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max-h-[calc(100%-140px)] overflow-hidden"><img alt="Mastering Service Level Objectives (SLOs): A Complete Guide" loading="lazy" decoding="async" data-nimg="fill" class="object-cover" style="position:absolute;height:100%;width:100%;left:0;top:0;right:0;bottom:0;color:transparent" sizes="100vw" srcSet="/_next/image?url=https%3A%2F%2Fa-us.storyblok.com%2Ff%2F1021527%2F6000x4000%2F749e4fc613%2Fslonew.png&amp;w=640&amp;q=75 640w, /_next/image?url=https%3A%2F%2Fa-us.storyblok.com%2Ff%2F1021527%2F6000x4000%2F749e4fc613%2Fslonew.png&amp;w=750&amp;q=75 750w, /_next/image?url=https%3A%2F%2Fa-us.storyblok.com%2Ff%2F1021527%2F6000x4000%2F749e4fc613%2Fslonew.png&amp;w=828&amp;q=75 828w, /_next/image?url=https%3A%2F%2Fa-us.storyblok.com%2Ff%2F1021527%2F6000x4000%2F749e4fc613%2Fslonew.png&amp;w=1080&amp;q=75 1080w, /_next/image?url=https%3A%2F%2Fa-us.storyblok.com%2Ff%2F1021527%2F6000x4000%2F749e4fc613%2Fslonew.png&amp;w=1200&amp;q=75 1200w, 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stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" class="lucide lucide-chevron-left size-4"><path d="m15 18-6-6 6-6"></path></svg> Back to <!-- -->Blog</a><div class="mb-5 flex flex-wrap gap-2"><span class="caption-2 flex h-6 w-fit items-center justify-center !text-nowrap rounded-full px-2 border border-white/20 bg-transparent">SRE</span></div><h1 class="heading-2 mb-6 mobile:mb-12">Mastering Service Level Objectives (SLOs): A Complete Guide</h1><div class="relative aspect-[1.8] w-full"><img alt="Mastering Service Level Objectives (SLOs): A Complete Guide" loading="lazy" decoding="async" data-nimg="fill" class="rounded-xl border border-white/20 object-cover" style="position:absolute;height:100%;width:100%;left:0;top:0;right:0;bottom:0;color:transparent" sizes="100vw" srcSet="/_next/image?url=https%3A%2F%2Fa-us.storyblok.com%2Ff%2F1021527%2F6000x4000%2F749e4fc613%2Fslonew.png&amp;w=640&amp;q=75 640w, /_next/image?url=https%3A%2F%2Fa-us.storyblok.com%2Ff%2F1021527%2F6000x4000%2F749e4fc613%2Fslonew.png&amp;w=750&amp;q=75 750w, /_next/image?url=https%3A%2F%2Fa-us.storyblok.com%2Ff%2F1021527%2F6000x4000%2F749e4fc613%2Fslonew.png&amp;w=828&amp;q=75 828w, /_next/image?url=https%3A%2F%2Fa-us.storyblok.com%2Ff%2F1021527%2F6000x4000%2F749e4fc613%2Fslonew.png&amp;w=1080&amp;q=75 1080w, /_next/image?url=https%3A%2F%2Fa-us.storyblok.com%2Ff%2F1021527%2F6000x4000%2F749e4fc613%2Fslonew.png&amp;w=1200&amp;q=75 1200w, /_next/image?url=https%3A%2F%2Fa-us.storyblok.com%2Ff%2F1021527%2F6000x4000%2F749e4fc613%2Fslonew.png&amp;w=1920&amp;q=75 1920w, /_next/image?url=https%3A%2F%2Fa-us.storyblok.com%2Ff%2F1021527%2F6000x4000%2F749e4fc613%2Fslonew.png&amp;w=2048&amp;q=75 2048w, /_next/image?url=https%3A%2F%2Fa-us.storyblok.com%2Ff%2F1021527%2F6000x4000%2F749e4fc613%2Fslonew.png&amp;w=3840&amp;q=75 3840w" src="/_next/image?url=https%3A%2F%2Fa-us.storyblok.com%2Ff%2F1021527%2F6000x4000%2F749e4fc613%2Fslonew.png&amp;w=3840&amp;q=75"/></div></div></section><section class="container-dark translate-y-[-50px] border-t border-border-2 p-0 pt-[110px] tablet:translate-y-[-140px] tablet:pt-[220px] opacity-100"><div class="container-fluid flex w-full max-w-[1060px] flex-col justify-between gap-10 py-0 text-w1 lg:flex-row tablet:px-14"><div class="flex w-full max-w-[632px] flex-col gap-3"><div><div class="flex items-center justify-between gap-4 border-b border-border-2 pb-5"><div class="flex flex-col gap-4 border-b mobile:flex-row mobile:gap-10 border-transparent pb-0"><div class="flex items-center gap-4"><img alt="Cortex" loading="lazy" width="40" height="40" decoding="async" data-nimg="1" class="size-10 rounded-[7px] border border-border-3 object-cover object-top" style="color:transparent" srcSet="/_next/image?url=https%3A%2F%2Fa-us.storyblok.com%2Ff%2F1021527%2F256x256%2F5c874a5b38%2Fcortex-icon.png&amp;w=48&amp;q=75 1x, /_next/image?url=https%3A%2F%2Fa-us.storyblok.com%2Ff%2F1021527%2F256x256%2F5c874a5b38%2Fcortex-icon.png&amp;w=96&amp;q=75 2x" src="/_next/image?url=https%3A%2F%2Fa-us.storyblok.com%2Ff%2F1021527%2F256x256%2F5c874a5b38%2Fcortex-icon.png&amp;w=96&amp;q=75"/><div class="flex flex-col justify-center gap-1"><p class="body-2">Cortex</p></div></div></div><p class="caption-2 text-w5 opacity-70">January 5, 2025</p></div></div><div class="flex flex-col"><article id="post-body" class="prose prose-lg max-w-none lg:pb-10"><p class="pb-4 mobile:pb-5 text-w2">As engineering teams scale their systems and adopt microservices architectures, maintaining consistent reliability becomes increasingly complex. <span>Service Level Objectives</span> (<span>SLOs</span>) help <a target="_blank" class="relative transition-all duration-500 will-change-[background-size] text-p2 bg-[linear-gradient(#B4A4EF,#B4A4EF)] bg-left-bottom bg-no-repeat bg-[length:0%_1px] hover:bg-[length:100%_1px]" href="https://www.cortex.io/post/what-is-sre-site-reliability-engineering"><span>site reliability engineers</span></a><a target="_blank" class="relative transition-all duration-500 will-change-[background-size] text-p2 bg-[linear-gradient(#B4A4EF,#B4A4EF)] bg-left-bottom bg-no-repeat bg-[length:0%_1px] hover:bg-[length:100%_1px]" href="https://www.cortex.io/post/what-is-sre-site-reliability-engineering"> (</a><a target="_blank" class="relative transition-all duration-500 will-change-[background-size] text-p2 bg-[linear-gradient(#B4A4EF,#B4A4EF)] bg-left-bottom bg-no-repeat bg-[length:0%_1px] hover:bg-[length:100%_1px]" href="https://www.cortex.io/post/what-is-sre-site-reliability-engineering"><span>SRE</span></a><a target="_blank" class="relative transition-all duration-500 will-change-[background-size] text-p2 bg-[linear-gradient(#B4A4EF,#B4A4EF)] bg-left-bottom bg-no-repeat bg-[length:0%_1px] hover:bg-[length:100%_1px]" href="https://www.cortex.io/post/what-is-sre-site-reliability-engineering">)</a> quantify reliability, make data-driven decisions about <span>service performance</span>, and keep everyone on track to achieve engineering excellence. </p><p class="pb-4 mobile:pb-5 text-w2">But implementing effective <span>SLOs</span> requires aligning engineering efforts with business outcomes. Whether you&#x27;re dealing with a handful of services or hundreds of microservices, understanding how to define <span>SLOs</span> and implement them effectively can mean the difference between proactive reliability management and reactive firefighting.</p><h2 id="what-are" class="subhead-1 pt-4 mobile:pt-5 pb-4 mobile:pb-5 clear-both"><b>What are </b><b><span>service level objectives</span></b><b> (</b><b><span>SLOs</span></b><b>)? </b></h2><p class="pb-4 mobile:pb-5 text-w2"><span>SLOs</span> are your engineering team&#x27;s internal commitment to <span>service reliability</span>. Think of them as the guardrails that help you balance feature velocity with system stability. <span>SLOs</span> provide visibility without which you run the risk of experiencing major <span>downtime</span> and not identifying issues until after they have severely impacted <span>user experience</span>.</p><p class="pb-4 mobile:pb-5 text-w2">They are often measured in terms of users’ satisfaction with the service, but the way that&#x27;s measured depends on the function and user expectations of the service. They can represent either business (e.g. runtime), technical (e.g. <span>dependencies</span>), or service (e.g. performance) <span>metrics</span>.</p><p class="pb-4 mobile:pb-5 text-w2">Consequently, an <span>SLO</span> is not the expectations themselves but the degree to which you want the product to meet those expectations. For example, you could set the expectations at 100%, but your <span>SLO</span> would be set at 98%, i.e., you would intend for the service to do what it is supposed to do and meet users’ expectations 98 out of 100 times.</p><p class="pb-4 mobile:pb-5 text-w2">While they&#x27;re not customer-facing commitments, they drive the technical decisions that ultimately impact the <span>user experience</span>. <span>SLOs</span> should be stricter than your <span>SLAs</span> to give you a buffer zone for addressing issues before they affect your contractual obligations.</p><h2 id="the-differences-between" class="subhead-1 pt-4 mobile:pt-5 pb-4 mobile:pb-5 clear-both"><b>The differences between </b><b><span>SLOs</span></b><b>, </b><b><span>SLAs</span></b><b>, and </b><b><span>SLIs</span></b></h2><p class="pb-4 mobile:pb-5 text-w2">The <a target="_blank" class="relative transition-all duration-500 will-change-[background-size] text-p2 bg-[linear-gradient(#B4A4EF,#B4A4EF)] bg-left-bottom bg-no-repeat bg-[length:0%_1px] hover:bg-[length:100%_1px]" href="https://www.cortex.io/post/the-top-3-mistakes-companies-make-with-slos-slas-and-slis">terms </a><a target="_blank" class="relative transition-all duration-500 will-change-[background-size] text-p2 bg-[linear-gradient(#B4A4EF,#B4A4EF)] bg-left-bottom bg-no-repeat bg-[length:0%_1px] hover:bg-[length:100%_1px]" href="https://www.cortex.io/post/the-top-3-mistakes-companies-make-with-slos-slas-and-slis"><span>SLO</span></a><a target="_blank" class="relative transition-all duration-500 will-change-[background-size] text-p2 bg-[linear-gradient(#B4A4EF,#B4A4EF)] bg-left-bottom bg-no-repeat bg-[length:0%_1px] hover:bg-[length:100%_1px]" href="https://www.cortex.io/post/the-top-3-mistakes-companies-make-with-slos-slas-and-slis">, </a><a target="_blank" class="relative transition-all duration-500 will-change-[background-size] text-p2 bg-[linear-gradient(#B4A4EF,#B4A4EF)] bg-left-bottom bg-no-repeat bg-[length:0%_1px] hover:bg-[length:100%_1px]" href="https://www.cortex.io/post/the-top-3-mistakes-companies-make-with-slos-slas-and-slis"><span>SLA</span></a><a target="_blank" class="relative transition-all duration-500 will-change-[background-size] text-p2 bg-[linear-gradient(#B4A4EF,#B4A4EF)] bg-left-bottom bg-no-repeat bg-[length:0%_1px] hover:bg-[length:100%_1px]" href="https://www.cortex.io/post/the-top-3-mistakes-companies-make-with-slos-slas-and-slis">, and </a><a target="_blank" class="relative transition-all duration-500 will-change-[background-size] text-p2 bg-[linear-gradient(#B4A4EF,#B4A4EF)] bg-left-bottom bg-no-repeat bg-[length:0%_1px] hover:bg-[length:100%_1px]" href="https://www.cortex.io/post/the-top-3-mistakes-companies-make-with-slos-slas-and-slis"><span>SLI</span></a> are often used interchangeably, but they&#x27;re quite different. Understanding the nuances can help you build effective <span>service reliability</span> practices.</p><h3 id="" class="subhead-2 pt-4 mobile:pt-5 pb-2 clear-both"><b><span>Service level agreements</span></b><b> (</b><b><span>SLAs</span></b><b>)</b></h3><p class="pb-4 mobile:pb-5 text-w2"><span>SLAs</span> translate your technical capabilities into business commitments. They&#x27;re the contracts you sign with customers that specify what happens when the <span>level of service</span> isn’t met. It&#x27;s important to keep enough space between your <span>SLOs</span> and <span>SLAs</span> to handle unexpected issues. If the product is unreliable and fails to meet certain requirements, it means the team has not met expectations. This can result in having to compensate the <span>end users</span>.</p><p class="pb-4 mobile:pb-5 text-w2">A common pattern is setting <span>SLOs</span> at least one order of magnitude tighter than your <span>SLAs</span>. For example, if your <span>SLA</span> promises 99.5% availability, your <span>SLO</span> might target 99.9%.</p><h3 id="" class="subhead-2 pt-4 mobile:pt-5 pb-2 clear-both"><b><span>Service level indicators</span></b><b> (</b><b><span>SLIs</span></b><b>)</b></h3><p class="pb-4 mobile:pb-5 text-w2"><span>SLIs</span> are where the rubber meets the road—they&#x27;re the actual <span>metrics</span> you track to determine if you&#x27;re meeting your objectives. Effective <span>SLIs</span> should directly measure what users experience. For example, instead of an internal <span>metric</span> like tracking <span>CPU</span> usage, measure <span>request latency</span>, which is what users actually feel. Here are some typical <span>SLIs</span>:</p><ul class="pb-4 mobile:pb-5 gap-3 mobile:gap-4 flex flex-col list-none [&amp;&gt;li&gt;.bullet-ul]:inline-block"><li class="[&amp;_p]:!body-2 [&amp;_p]:!p-0 flex gap-3"><span class="bullet-ul mx-1 my-1.5 hidden size-2 shrink-0 bg-p6"></span><span class="bullet-ol caption-1 my-0.5 hidden size-4 shrink-0 items-center justify-center rounded-full bg-p6 text-white">1</span><div class="flex flex-col gap-2.5"><p class="pb-4 mobile:pb-5 text-w2"><span>Request latency</span> from the user&#x27;s perspective</p></div></li><li class="[&amp;_p]:!body-2 [&amp;_p]:!p-0 flex gap-3"><span class="bullet-ul mx-1 my-1.5 hidden size-2 shrink-0 bg-p6"></span><span class="bullet-ol caption-1 my-0.5 hidden size-4 shrink-0 items-center justify-center rounded-full bg-p6 text-white">2</span><div class="flex flex-col gap-2.5"><p class="pb-4 mobile:pb-5 text-w2"><span>Error rates</span> across critical user journeys</p></div></li><li class="[&amp;_p]:!body-2 [&amp;_p]:!p-0 flex gap-3"><span class="bullet-ul mx-1 my-1.5 hidden size-2 shrink-0 bg-p6"></span><span class="bullet-ol caption-1 my-0.5 hidden size-4 shrink-0 items-center justify-center rounded-full bg-p6 text-white">3</span><div class="flex flex-col gap-2.5"><p class="pb-4 mobile:pb-5 text-w2">System <span>throughput</span> during peak loads</p></div></li><li class="[&amp;_p]:!body-2 [&amp;_p]:!p-0 flex gap-3"><span class="bullet-ul mx-1 my-1.5 hidden size-2 shrink-0 bg-p6"></span><span class="bullet-ol caption-1 my-0.5 hidden size-4 shrink-0 items-center justify-center rounded-full bg-p6 text-white">4</span><div class="flex flex-col gap-2.5"><p class="pb-4 mobile:pb-5 text-w2">Availability of key business functions</p></div></li><li class="[&amp;_p]:!body-2 [&amp;_p]:!p-0 flex gap-3"><span class="bullet-ul mx-1 my-1.5 hidden size-2 shrink-0 bg-p6"></span><span class="bullet-ol caption-1 my-0.5 hidden size-4 shrink-0 items-center justify-center rounded-full bg-p6 text-white">5</span><div class="flex flex-col gap-2.5"><p class="pb-4 mobile:pb-5 text-w2">Data durability for critical user information</p></div></li></ul><h2 id="how-to-define-and-set-effective" class="subhead-1 pt-4 mobile:pt-5 pb-4 mobile:pb-5 clear-both"><b>How to define and set effective </b><b><span>SLOs</span></b><b>: 4 steps</b></h2><p class="pb-4 mobile:pb-5 text-w2">Many teams either aim too high (creating unnecessary operational burden) or too low (risking <span>user satisfaction</span>) when they&#x27;re setting <span>SLOs</span>. While every company operates slightly differently, there are some universal steps that all teams can follow to establish a strong foundation.</p><h3 id="1-understand-your-customers-needs" class="subhead-2 pt-4 mobile:pt-5 pb-2 clear-both"><b>1. Understand your customers&#x27; needs</b></h3><p class="pb-4 mobile:pb-5 text-w2">Setting <span>SLOs</span> starts with understanding what reliability means to your users. Engineers often focus on technical <span>metrics</span> like <span>uptime</span> or <span>response time</span>, but customer experience is more nuanced. </p><p class="pb-4 mobile:pb-5 text-w2">To translate customer needs into meaningful <span>SLOs</span>, start by looking at user behavior patterns, common customer incident reports, and session data to understand user dropoff. Talk to customer success teams about common reliability complaints and get feedback from sales teams about competitive deals where reliability was the pain point. </p><p class="pb-4 mobile:pb-5 text-w2">Take into account the different reliability requirements of users. For instance, an e-commerce checkout service needs stricter <span>SLOs</span> than a product recommendation engine. Map your services to business impact:</p><ul class="pb-4 mobile:pb-5 gap-3 mobile:gap-4 flex flex-col list-none [&amp;&gt;li&gt;.bullet-ul]:inline-block"><li class="[&amp;_p]:!body-2 [&amp;_p]:!p-0 flex gap-3"><span class="bullet-ul mx-1 my-1.5 hidden size-2 shrink-0 bg-p6"></span><span class="bullet-ol caption-1 my-0.5 hidden size-4 shrink-0 items-center justify-center rounded-full bg-p6 text-white">1</span><div class="flex flex-col gap-2.5"><p class="pb-4 mobile:pb-5 text-w2">High-impact services (payment processing, user authentication): Set aggressive <span>SLOs</span></p></div></li><li class="[&amp;_p]:!body-2 [&amp;_p]:!p-0 flex gap-3"><span class="bullet-ul mx-1 my-1.5 hidden size-2 shrink-0 bg-p6"></span><span class="bullet-ol caption-1 my-0.5 hidden size-4 shrink-0 items-center justify-center rounded-full bg-p6 text-white">2</span><div class="flex flex-col gap-2.5"><p class="pb-4 mobile:pb-5 text-w2">Medium-impact services (search, product listings): Balance reliability with cost</p></div></li><li class="[&amp;_p]:!body-2 [&amp;_p]:!p-0 flex gap-3"><span class="bullet-ul mx-1 my-1.5 hidden size-2 shrink-0 bg-p6"></span><span class="bullet-ol caption-1 my-0.5 hidden size-4 shrink-0 items-center justify-center rounded-full bg-p6 text-white">3</span><div class="flex flex-col gap-2.5"><p class="pb-4 mobile:pb-5 text-w2">Low-impact services (analytics, reporting): Set more relaxed objectives</p></div></li></ul><h3 id="2-set-baseline" class="subhead-2 pt-4 mobile:pt-5 pb-2 clear-both"><b>2. Set baseline </b><b><span>metrics</span></b></h3><p class="pb-4 mobile:pb-5 text-w2">Many teams make the mistake of setting <span>SLO targets</span> before understanding their current performance. This approach often leads to unrealistic objectives that either create unnecessary stress or get ignored entirely. Instead, get at least 30 days of historical performance data, and look for patterns in your existing <span>metrics</span> and external factors that influence performance.</p><p class="pb-4 mobile:pb-5 text-w2">It&#x27;s important to distinguish between normal variance and actual issues. Your baseline measurements should help you understand what &quot;normal&quot; looks like for your services, including expected peak loads and seasonal patterns.</p><h3 id="3-define" class="subhead-2 pt-4 mobile:pt-5 pb-2 clear-both"><b>3. Define </b><b><span>SLIs</span></b><b> and </b><b><span>error budgets</span></b></h3><p class="pb-4 mobile:pb-5 text-w2">While <span>SLOs</span> are the targets that you hope to reach, <span>service level indicators</span> are quantitative measures or <span>metrics</span> that help determine the actual <span>quality of service</span> being delivered to users. You are probably already tracking all sorts of <span>metrics</span>, but we recommend selecting a few that are especially reflective of <span>user experience</span> to be marked as <span>SLIs</span>.</p><p class="pb-4 mobile:pb-5 text-w2">Many <span>metrics</span>, such as <span>CPU</span> usage, do not directly impact the <span>users’ experience</span> of your product and will not make for helpful <span>SLIs</span>. Only <span>metrics</span> that demonstrate a strong relationship with the degree to which your users are satisfied are worth considering.</p><p class="pb-4 mobile:pb-5 text-w2">Once you have baseline data, you can set meaningful targets and <span>error budgets</span>. An <span>error budget</span> is a measure of the number of negative events you can have on a <span>metric</span> before your <span>SLO</span> is considered to have been violated. It&#x27;s the gap between perfect reliability (100%) and your <span>SLO target</span>. Identifying the <span>error budget</span> can also take some experimentation as you figure out how to define the scope of reliability for your product. </p><h3 id="4-iterate-and-refine" class="subhead-2 pt-4 mobile:pt-5 pb-2 clear-both"><b>4. Iterate and refine</b></h3><p class="pb-4 mobile:pb-5 text-w2"><span>SLOs</span> need regular refinement, so schedule regular time to review <span>SLO</span> performance monthly with <span>stakeholders</span> and adjust thresholds based on customer feedback. Make sure to document the reasoning behind each change, so you have a record for future reference. </p><p class="pb-4 mobile:pb-5 text-w2">Refinement is a fine balance between keeping <span>SLOs</span> consistent enough to be meaningful and updating them when business needs change. </p><h2 id="essential" class="subhead-1 pt-4 mobile:pt-5 pb-4 mobile:pb-5 clear-both"><b>Essential </b><b><span>metrics</span></b><b> for </b><b><span>SLO</span></b><b> management</b></h2><p class="pb-4 mobile:pb-5 text-w2">While every service is different, certain <span>metrics</span> are consistently valuable across different architectures and use cases. Start with these types of <span>metrics</span> that directly impact <span>user experience</span>:</p><ul class="pb-4 mobile:pb-5 gap-3 mobile:gap-4 flex flex-col list-none [&amp;&gt;li&gt;.bullet-ul]:inline-block"><li class="[&amp;_p]:!body-2 [&amp;_p]:!p-0 flex gap-3"><span class="bullet-ul mx-1 my-1.5 hidden size-2 shrink-0 bg-p6"></span><span class="bullet-ol caption-1 my-0.5 hidden size-4 shrink-0 items-center justify-center rounded-full bg-p6 text-white">1</span><div class="flex flex-col gap-2.5"><p class="pb-4 mobile:pb-5 text-w2"><span>Latency</span> <span>metrics</span>, such as time to first byte for content delivery and <span>backend</span> processing duration</p></div></li><li class="[&amp;_p]:!body-2 [&amp;_p]:!p-0 flex gap-3"><span class="bullet-ul mx-1 my-1.5 hidden size-2 shrink-0 bg-p6"></span><span class="bullet-ol caption-1 my-0.5 hidden size-4 shrink-0 items-center justify-center rounded-full bg-p6 text-white">2</span><div class="flex flex-col gap-2.5"><p class="pb-4 mobile:pb-5 text-w2">Availability <span>metrics</span>, such as success rate of <span>API</span> requests and failed transaction percentage </p></div></li><li class="[&amp;_p]:!body-2 [&amp;_p]:!p-0 flex gap-3"><span class="bullet-ul mx-1 my-1.5 hidden size-2 shrink-0 bg-p6"></span><span class="bullet-ol caption-1 my-0.5 hidden size-4 shrink-0 items-center justify-center rounded-full bg-p6 text-white">3</span><div class="flex flex-col gap-2.5"><p class="pb-4 mobile:pb-5 text-w2">Traffic <span>metrics</span>, such as concurrent user sessions and network <span>throughput</span> </p></div></li><li class="[&amp;_p]:!body-2 [&amp;_p]:!p-0 flex gap-3"><span class="bullet-ul mx-1 my-1.5 hidden size-2 shrink-0 bg-p6"></span><span class="bullet-ol caption-1 my-0.5 hidden size-4 shrink-0 items-center justify-center rounded-full bg-p6 text-white">4</span><div class="flex flex-col gap-2.5"><p class="pb-4 mobile:pb-5 text-w2">Resource utilization, such as <span>CPU</span> and memory usage patterns</p></div></li><li class="[&amp;_p]:!body-2 [&amp;_p]:!p-0 flex gap-3"><span class="bullet-ul mx-1 my-1.5 hidden size-2 shrink-0 bg-p6"></span><span class="bullet-ol caption-1 my-0.5 hidden size-4 shrink-0 items-center justify-center rounded-full bg-p6 text-white">5</span><div class="flex flex-col gap-2.5"><p class="pb-4 mobile:pb-5 text-w2"><span>User experience</span>, such as customer satisfaction (CSAT) scores </p></div></li><li class="[&amp;_p]:!body-2 [&amp;_p]:!p-0 flex gap-3"><span class="bullet-ul mx-1 my-1.5 hidden size-2 shrink-0 bg-p6"></span><span class="bullet-ol caption-1 my-0.5 hidden size-4 shrink-0 items-center justify-center rounded-full bg-p6 text-white">6</span><div class="flex flex-col gap-2.5"><p class="pb-4 mobile:pb-5 text-w2">Business performance, such as revenue impact during degraded performance</p></div></li></ul><p class="pb-4 mobile:pb-5 text-w2">In microservices environments, internal developer portals (IDPs) help track service health across numerous components. They help teams maintain visibility into <span>service performance</span> and quickly identify potential issues before they impact customers.</p><h2 id="best-practices-for-implementing" class="subhead-1 pt-4 mobile:pt-5 pb-4 mobile:pb-5 clear-both"><b>Best practices for implementing </b><b><span>SLOs</span></b></h2><p class="pb-4 mobile:pb-5 text-w2">Teams often struggle with inconsistent measurement, unclear ownership, and difficulty maintaining <span>SLOs</span> as systems evolve. These best practices will help set up your <span>SLOs</span> for success:</p><h3 id="use-an-internal-developer-portal" class="subhead-2 pt-4 mobile:pt-5 pb-2 clear-both"><b>Use an internal developer portal</b></h3><p class="pb-4 mobile:pb-5 text-w2">An IDP serves as the single source of truth for your <span>SLOs</span> by centralizing all definitions and current performance <span>metrics</span> in one location. It helps teams track service <span>dependencies</span> and their impact on composite <span>SLOs</span> while automating essential reporting and alert management functions. Teams can see the historical context for <span>SLO</span> decisions, so they can make informed decisions about future modifications.</p><h3 id="automate" class="subhead-2 pt-4 mobile:pt-5 pb-2 clear-both"><b>Automate </b><b><span>SLO</span></b><b> tracking</b></h3><p class="pb-4 mobile:pb-5 text-w2">Implement automated data collection for all <span>SLIs</span> to ensure tracking is consistent and reliable. <span>Real-time</span> dashboards and intelligent alerting based on <span>error budget</span> burn rates help teams identify issues before they become critical. </p><h3 id="establish-clear-ownership" class="subhead-2 pt-4 mobile:pt-5 pb-2 clear-both"><b>Establish clear ownership</b></h3><p class="pb-4 mobile:pb-5 text-w2">Assign primary team responsibility for each <span>SLO</span> and define explicit ownership for shared <span>dependencies</span> to prevent confusion during incidents. Create clear escalation paths for <span>SLO</span> breaches that specify who should be notified and when.</p><h3 id="involve" class="subhead-2 pt-4 mobile:pt-5 pb-2 clear-both"><b>Involve </b><b><span>stakeholders</span></b><b> early</b></h3><p class="pb-4 mobile:pb-5 text-w2">Include <span>product managers</span> in <span>SLO target</span> discussions to ensure alignment with <span>business goals</span> and <span>customer expectations</span>. Customer success teams can give valuable perspective on user impact, so involve them early on and regularly review <span>SLOs</span> to make sure they&#x27;re aligned with business priorities. </p><h3 id="segment" class="subhead-2 pt-4 mobile:pt-5 pb-2 clear-both"><b>Segment </b><b><span>SLOs</span></b><b> by service type</b></h3><p class="pb-4 mobile:pb-5 text-w2">Define service tiers based on business impact and set appropriate <span>SLOs</span> for each tier rather than applying one-size-fits-all targets. Consider regional variations in service requirements and account for different customer segments when setting reliability targets. This helps teams focus their reliability efforts where they matter most.</p><h3 id="incorporate-redundancy" class="subhead-2 pt-4 mobile:pt-5 pb-2 clear-both"><b>Incorporate redundancy</b></h3><p class="pb-4 mobile:pb-5 text-w2">Build reliability into your architecture by implementing circuit breakers for critical <span>dependencies</span> and deploying services across multiple availability zones. Design systems for graceful degradation with fallback options for critical functionality to maintain <span>service availability</span> even during partial <span>outages</span>.</p><h3 id="document-and-communicate" class="subhead-2 pt-4 mobile:pt-5 pb-2 clear-both"><b>Document and communicate</b></h3><p class="pb-4 mobile:pb-5 text-w2">Maintain up-to-date <span>SLO</span> definitions and measurement methods in a central location accessible to all teams. Create clear incident response playbooks that guide teams through common failure scenarios and share regular <span>SLO</span> performance reports to maintain visibility across the organization.</p><h2 id="set-up-accurate" class="subhead-1 pt-4 mobile:pt-5 pb-4 mobile:pb-5 clear-both"><b>Set up accurate </b><b><span>SLOs</span></b><b> fast with Cortex</b></h2><p class="pb-4 mobile:pb-5 text-w2">While implementing <span>SLOs</span> can be complex, the right tooling makes a difference in setup and maintenance. Cortex helps teams implement and manage <span>SLOs</span> effectively across their microservices architecture. Here&#x27;s how leading teams are using Cortex to improve their <span>SLOs</span>:</p><h3 id="engineering-excellence-through-connected-insights" class="subhead-2 pt-4 mobile:pt-5 pb-2 clear-both"><b>Engineering excellence through connected insights</b></h3><p class="pb-4 mobile:pb-5 text-w2">Cortex connects engineering output to business outcomes by providing comprehensive visibility into system and team performance. The <a target="_blank" class="relative transition-all duration-500 will-change-[background-size] text-p2 bg-[linear-gradient(#B4A4EF,#B4A4EF)] bg-left-bottom bg-no-repeat bg-[length:0%_1px] hover:bg-[length:100%_1px]" href="https://www.cortex.io/products/eng-intelligence">Eng Intelligence feature</a> leverages your existing <span>SLO</span> data to help teams measure and improve their effectiveness. This <span>integration</span> between reliability <span>metrics</span> and team performance creates a feedback loop that drives continuous improvement and engineering excellence.</p><h3 id="unified-service-visibility" class="subhead-2 pt-4 mobile:pt-5 pb-2 clear-both"><b>Unified service visibility</b></h3><p class="pb-4 mobile:pb-5 text-w2"><a target="_blank" class="relative transition-all duration-500 will-change-[background-size] text-p2 bg-[linear-gradient(#B4A4EF,#B4A4EF)] bg-left-bottom bg-no-repeat bg-[length:0%_1px] hover:bg-[length:100%_1px]" href="https://www.cortex.io/products/catalog">Cortex&#x27;s service catalog</a> provides a complete view of your microservices landscape in a single location. Teams can visualize service <span>dependencies</span>, track ownership, and monitor critical <span>metrics</span> from one central dashboard. This helps teams understand how their <span>SLOs</span> interact with dependent services and quickly identify potential reliability issues before they affect customers.</p><h3 id="automated-reliability-tracking" class="subhead-2 pt-4 mobile:pt-5 pb-2 clear-both"><b>Automated reliability tracking</b></h3><p class="pb-4 mobile:pb-5 text-w2">Cortex automates tracking <span>SLO</span> compliance through scorecards that continuously evaluate service health against predefined objectives. Teams receive <span>real-time</span> insights into <span>service performance</span> and can quickly identify when services drift from their reliability targets.</p><h3 id="streamlined-incident-management" class="subhead-2 pt-4 mobile:pt-5 pb-2 clear-both"><b>Streamlined incident management</b></h3><p class="pb-4 mobile:pb-5 text-w2">When incidents occur, context is critical. Cortex integrates with your existing <a target="_blank" class="relative transition-all duration-500 will-change-[background-size] text-p2 bg-[linear-gradient(#B4A4EF,#B4A4EF)] bg-left-bottom bg-no-repeat bg-[length:0%_1px] hover:bg-[length:100%_1px]" href="https://www.cortex.io/solutions/incident-management">incident management</a> tools to provide immediate access to relevant service information, <span>dependencies</span>, and historical performance data. Teams can correlate <span>SLO</span> breaches with root causes more quickly, leading to faster resolution times and more effective post-incident learning.</p><h3 id="production-readiness-assessment" class="subhead-2 pt-4 mobile:pt-5 pb-2 clear-both"><b>Production readiness assessment</b></h3><p class="pb-4 mobile:pb-5 text-w2">Before setting <span>SLOs</span>, teams need confidence that their services are ready for production traffic. Cortex provides built-in tools for assessing service <a target="_blank" class="relative transition-all duration-500 will-change-[background-size] text-p2 bg-[linear-gradient(#B4A4EF,#B4A4EF)] bg-left-bottom bg-no-repeat bg-[length:0%_1px] hover:bg-[length:100%_1px]" href="https://www.cortex.io/post/how-to-create-a-great-production-readiness-checklist">production readiness</a>, ensuring all necessary components and <span>metrics</span> are in place. This systematic approach helps teams set realistic and achievable <span>SLOs</span> while maintaining high reliability standards.</p><h3 id="standardized" class="subhead-2 pt-4 mobile:pt-5 pb-2 clear-both"><b>Standardized </b><b><span>SLO</span></b><b> implementation</b></h3><p class="pb-4 mobile:pb-5 text-w2"><a target="_blank" class="relative transition-all duration-500 will-change-[background-size] text-p2 bg-[linear-gradient(#B4A4EF,#B4A4EF)] bg-left-bottom bg-no-repeat bg-[length:0%_1px] hover:bg-[length:100%_1px]" href="https://www.cortex.io/post/improve-velocity-and-reliability-through-service-standardization">Consistency</a> in <span>SLO</span> implementation becomes increasingly important as your service count grows. Cortex&#x27;s platform provides templates and workflow <span>automation</span> that help teams standardize their approach to <span>SLO</span> definition and management. This standardization reduces setup time and ensures consistent reliability practices across all services.</p><p class="pb-4 mobile:pb-5 text-w2">To learn more about Cortex, <a target="_blank" class="relative transition-all duration-500 will-change-[background-size] text-p2 bg-[linear-gradient(#B4A4EF,#B4A4EF)] bg-left-bottom bg-no-repeat bg-[length:0%_1px] hover:bg-[length:100%_1px]" href="https://www.cortex.io/demo">book a demo</a>.</p></article></div></div><aside class="relative flex w-full max-w-full flex-row gap-10 self-stretch tablet:max-w-[308px] tablet:flex-col"><div class="absolute left-0 top-[-110px] hidden h-[calc(100%+110px)] w-px bg-border-2 tablet:top-[-220px] tablet:block tablet:h-[calc(100%+220px)]"></div><div class="top-[110px] flex w-full flex-col self-start mobile:top-[240px] lg:w-auto tablet:sticky tablet:pt-[0px]"><div class="flex flex-col gap-3 pt-6 tablet:pl-7"><h5 class="caption-2 text-w2">Get in touch with Cortex</h5><div class="group/main relative"><a 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engineering teams scale their systems and adopt microservices architectures, maintaining consistent reliability becomes increasingly complex. \",\"type\":\"text\"},{\"text\":\"Service Level Objectives\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" (\",\"type\":\"text\"},{\"text\":\"SLOs\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\") help \",\"type\":\"text\"},{\"text\":\"site reliability engineers\",\"type\":\"text\",\"marks\":[{\"type\":\"link\",\"attrs\":{\"href\":\"https://www.cortex.io/post/what-is-sre-site-reliability-engineering\",\"uuid\":null,\"anchor\":null,\"target\":null,\"linktype\":\"url\"}},{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" (\",\"type\":\"text\",\"marks\":[{\"type\":\"link\",\"attrs\":{\"href\":\"https://www.cortex.io/post/what-is-sre-site-reliability-engineering\",\"uuid\":null,\"anchor\":null,\"target\":null,\"linktype\":\"url\"}}]},{\"text\":\"SRE\",\"type\":\"text\",\"marks\":[{\"type\":\"link\",\"attrs\":{\"href\":\"https://www.cortex.io/post/what-is-sre-site-reliability-engineering\",\"uuid\":null,\"anchor\":null,\"target\":null,\"linktype\":\"url\"}},{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\")\",\"type\":\"text\",\"marks\":[{\"type\":\"link\",\"attrs\":{\"href\":\"https://www.cortex.io/post/what-is-sre-site-reliability-engineering\",\"uuid\":null,\"anchor\":null,\"target\":null,\"linktype\":\"url\"}}]},{\"text\":\" quantify reliability, make data-driven decisions about \",\"type\":\"text\"},{\"text\":\"service performance\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\", and keep everyone on track to achieve engineering excellence. \",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"content\":[{\"text\":\"But implementing effective \",\"type\":\"text\"},{\"text\":\"SLOs\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" requires aligning engineering efforts with business outcomes. Whether you're dealing with a handful of services or hundreds of microservices, understanding how to define \",\"type\":\"text\"},{\"text\":\"SLOs\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" and implement them effectively can mean the difference between proactive reliability management and reactive firefighting.\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":2},\"content\":[{\"text\":\"What are \",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]},{\"text\":\"service level objectives\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"},{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" (\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]},{\"text\":\"SLOs\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"},{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\")? \",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"content\":[{\"text\":\"SLOs\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" are your engineering team's internal commitment to \",\"type\":\"text\"},{\"text\":\"service reliability\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\". Think of them as the guardrails that help you balance feature velocity with system stability. \",\"type\":\"text\"},{\"text\":\"SLOs\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" provide visibility without which you run the risk of experiencing major \",\"type\":\"text\"},{\"text\":\"downtime\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" and not identifying issues until after they have severely impacted \",\"type\":\"text\"},{\"text\":\"user experience\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\".\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"content\":[{\"text\":\"They are often measured in terms of users’ satisfaction with the service, but the way that's measured depends on the function and user expectations of the service. They can represent either business (e.g. runtime), technical (e.g. \",\"type\":\"text\"},{\"text\":\"dependencies\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\"), or service (e.g. performance) \",\"type\":\"text\"},{\"text\":\"metrics\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\".\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"content\":[{\"text\":\"Consequently, an \",\"type\":\"text\"},{\"text\":\"SLO\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" is not the expectations themselves but the degree to which you want the product to meet those expectations. 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Understanding the nuances can help you build effective \",\"type\":\"text\"},{\"text\":\"service reliability\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" practices.\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":3},\"content\":[{\"text\":\"Service level agreements\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"},{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" (\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]},{\"text\":\"SLAs\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"},{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\")\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"content\":[{\"text\":\"SLAs\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" translate your technical capabilities into business commitments. They're the contracts you sign with customers that specify what happens when the \",\"type\":\"text\"},{\"text\":\"level of service\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" isn’t met. It's important to keep enough space between your \",\"type\":\"text\"},{\"text\":\"SLOs\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" and \",\"type\":\"text\"},{\"text\":\"SLAs\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" to handle unexpected issues. If the product is unreliable and fails to meet certain requirements, it means the team has not met expectations. This can result in having to compensate the \",\"type\":\"text\"},{\"text\":\"end users\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\".\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"content\":[{\"text\":\"A common pattern is setting \",\"type\":\"text\"},{\"text\":\"SLOs\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" at least one order of magnitude tighter than your \",\"type\":\"text\"},{\"text\":\"SLAs\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\". For example, if your \",\"type\":\"text\"},{\"text\":\"SLA\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" promises 99.5% availability, your \",\"type\":\"text\"},{\"text\":\"SLO\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" might target 99.9%.\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":3},\"content\":[{\"text\":\"Service level indicators\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"},{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" (\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]},{\"text\":\"SLIs\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"},{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\")\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"content\":[{\"text\":\"SLIs\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" are where the rubber meets the road—they're the actual \",\"type\":\"text\"},{\"text\":\"metrics\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" you track to determine if you're meeting your objectives. Effective \",\"type\":\"text\"},{\"text\":\"SLIs\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" should directly measure what users experience. For example, instead of an internal \",\"type\":\"text\"},{\"text\":\"metric\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" like tracking \",\"type\":\"text\"},{\"text\":\"CPU\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" usage, measure \",\"type\":\"text\"},{\"text\":\"request latency\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\", which is what users actually feel. Here are some typical \",\"type\":\"text\"},{\"text\":\"SLIs\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\":\",\"type\":\"text\"}]},{\"type\":\"bullet_list\",\"content\":[{\"type\":\"list_item\",\"content\":[{\"type\":\"paragraph\",\"content\":[{\"text\":\"Request latency\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" from the user's perspective\",\"type\":\"text\"}]}]},{\"type\":\"list_item\",\"content\":[{\"type\":\"paragraph\",\"content\":[{\"text\":\"Error rates\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" across critical user journeys\",\"type\":\"text\"}]}]},{\"type\":\"list_item\",\"content\":[{\"type\":\"paragraph\",\"content\":[{\"text\":\"System \",\"type\":\"text\"},{\"text\":\"throughput\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" during peak loads\",\"type\":\"text\"}]}]},{\"type\":\"list_item\",\"content\":[{\"type\":\"paragraph\",\"content\":[{\"text\":\"Availability of key business functions\",\"type\":\"text\"}]}]},{\"type\":\"list_item\",\"content\":[{\"type\":\"paragraph\",\"content\":[{\"text\":\"Data durability for critical user information\",\"type\":\"text\"}]}]}]},{\"type\":\"heading\",\"attrs\":{\"level\":2},\"content\":[{\"text\":\"How to define and set effective \",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]},{\"text\":\"SLOs\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"},{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\": 4 steps\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"content\":[{\"text\":\"Many teams either aim too high (creating unnecessary operational burden) or too low (risking \",\"type\":\"text\"},{\"text\":\"user satisfaction\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\") when they're setting \",\"type\":\"text\"},{\"text\":\"SLOs\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\". While every company operates slightly differently, there are some universal steps that all teams can follow to establish a strong foundation.\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":3},\"content\":[{\"text\":\"1. Understand your customers' needs\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"content\":[{\"text\":\"Setting \",\"type\":\"text\"},{\"text\":\"SLOs\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" starts with understanding what reliability means to your users. Engineers often focus on technical \",\"type\":\"text\"},{\"text\":\"metrics\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" like \",\"type\":\"text\"},{\"text\":\"uptime\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" or \",\"type\":\"text\"},{\"text\":\"response time\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\", but customer experience is more nuanced. \",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"content\":[{\"text\":\"To translate customer needs into meaningful \",\"type\":\"text\"},{\"text\":\"SLOs\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\", start by looking at user behavior patterns, common customer incident reports, and session data to understand user dropoff. Talk to customer success teams about common reliability complaints and get feedback from sales teams about competitive deals where reliability was the pain point. \",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"content\":[{\"text\":\"Take into account the different reliability requirements of users. For instance, an e-commerce checkout service needs stricter \",\"type\":\"text\"},{\"text\":\"SLOs\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" than a product recommendation engine. Map your services to business impact:\",\"type\":\"text\"}]},{\"type\":\"bullet_list\",\"content\":[{\"type\":\"list_item\",\"content\":[{\"type\":\"paragraph\",\"content\":[{\"text\":\"High-impact services (payment processing, user authentication): Set aggressive \",\"type\":\"text\"},{\"text\":\"SLOs\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]}]}]},{\"type\":\"list_item\",\"content\":[{\"type\":\"paragraph\",\"content\":[{\"text\":\"Medium-impact services (search, product listings): Balance reliability with cost\",\"type\":\"text\"}]}]},{\"type\":\"list_item\",\"content\":[{\"type\":\"paragraph\",\"content\":[{\"text\":\"Low-impact services (analytics, reporting): Set more relaxed objectives\",\"type\":\"text\"}]}]}]},{\"type\":\"heading\",\"attrs\":{\"level\":3},\"content\":[{\"text\":\"2. Set baseline \",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]},{\"text\":\"metrics\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"},{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]}]},{\"type\":\"paragraph\",\"content\":[{\"text\":\"Many teams make the mistake of setting \",\"type\":\"text\"},{\"text\":\"SLO targets\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" before understanding their current performance. This approach often leads to unrealistic objectives that either create unnecessary stress or get ignored entirely. Instead, get at least 30 days of historical performance data, and look for patterns in your existing \",\"type\":\"text\"},{\"text\":\"metrics\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" and external factors that influence performance.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"content\":[{\"text\":\"It's important to distinguish between normal variance and actual issues. Your baseline measurements should help you understand what \\\"normal\\\" looks like for your services, including expected peak loads and seasonal patterns.\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":3},\"content\":[{\"text\":\"3. Define \",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]},{\"text\":\"SLIs\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"},{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" and \",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]},{\"text\":\"error budgets\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"},{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]}]},{\"type\":\"paragraph\",\"content\":[{\"text\":\"While \",\"type\":\"text\"},{\"text\":\"SLOs\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" are the targets that you hope to reach, \",\"type\":\"text\"},{\"text\":\"service level indicators\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" are quantitative measures or \",\"type\":\"text\"},{\"text\":\"metrics\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" that help determine the actual \",\"type\":\"text\"},{\"text\":\"quality of service\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" being delivered to users. You are probably already tracking all sorts of \",\"type\":\"text\"},{\"text\":\"metrics\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\", but we recommend selecting a few that are especially reflective of \",\"type\":\"text\"},{\"text\":\"user experience\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" to be marked as \",\"type\":\"text\"},{\"text\":\"SLIs\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\".\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"content\":[{\"text\":\"Many \",\"type\":\"text\"},{\"text\":\"metrics\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\", such as \",\"type\":\"text\"},{\"text\":\"CPU\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" usage, do not directly impact the \",\"type\":\"text\"},{\"text\":\"users’ experience\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" of your product and will not make for helpful \",\"type\":\"text\"},{\"text\":\"SLIs\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\". Only \",\"type\":\"text\"},{\"text\":\"metrics\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" that demonstrate a strong relationship with the degree to which your users are satisfied are worth considering.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"content\":[{\"text\":\"Once you have baseline data, you can set meaningful targets and \",\"type\":\"text\"},{\"text\":\"error budgets\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\". An \",\"type\":\"text\"},{\"text\":\"error budget\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" is a measure of the number of negative events you can have on a \",\"type\":\"text\"},{\"text\":\"metric\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" before your \",\"type\":\"text\"},{\"text\":\"SLO\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" is considered to have been violated. It's the gap between perfect reliability (100%) and your \",\"type\":\"text\"},{\"text\":\"SLO target\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\". Identifying the \",\"type\":\"text\"},{\"text\":\"error budget\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" can also take some experimentation as you figure out how to define the scope of reliability for your product. \",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":3},\"content\":[{\"text\":\"4. Iterate and refine\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"content\":[{\"text\":\"SLOs\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" need regular refinement, so schedule regular time to review \",\"type\":\"text\"},{\"text\":\"SLO\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" performance monthly with \",\"type\":\"text\"},{\"text\":\"stakeholders\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" and adjust thresholds based on customer feedback. Make sure to document the reasoning behind each change, so you have a record for future reference. \",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"content\":[{\"text\":\"Refinement is a fine balance between keeping \",\"type\":\"text\"},{\"text\":\"SLOs\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" consistent enough to be meaningful and updating them when business needs change. \",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":2},\"content\":[{\"text\":\"Essential \",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]},{\"text\":\"metrics\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"},{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" for \",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]},{\"text\":\"SLO\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"},{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" management\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"content\":[{\"text\":\"While every service is different, certain \",\"type\":\"text\"},{\"text\":\"metrics\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" are consistently valuable across different architectures and use cases. Start with these types of \",\"type\":\"text\"},{\"text\":\"metrics\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" that directly impact \",\"type\":\"text\"},{\"text\":\"user experience\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\":\",\"type\":\"text\"}]},{\"type\":\"bullet_list\",\"content\":[{\"type\":\"list_item\",\"content\":[{\"type\":\"paragraph\",\"content\":[{\"text\":\"Latency\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" \",\"type\":\"text\"},{\"text\":\"metrics\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\", such as time to first byte for content delivery and \",\"type\":\"text\"},{\"text\":\"backend\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" processing duration\",\"type\":\"text\"}]}]},{\"type\":\"list_item\",\"content\":[{\"type\":\"paragraph\",\"content\":[{\"text\":\"Availability \",\"type\":\"text\"},{\"text\":\"metrics\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\", such as success rate of \",\"type\":\"text\"},{\"text\":\"API\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" requests and failed transaction percentage \",\"type\":\"text\"}]}]},{\"type\":\"list_item\",\"content\":[{\"type\":\"paragraph\",\"content\":[{\"text\":\"Traffic \",\"type\":\"text\"},{\"text\":\"metrics\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\", such as concurrent user sessions and network \",\"type\":\"text\"},{\"text\":\"throughput\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" \",\"type\":\"text\"}]}]},{\"type\":\"list_item\",\"content\":[{\"type\":\"paragraph\",\"content\":[{\"text\":\"Resource utilization, such as \",\"type\":\"text\"},{\"text\":\"CPU\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" and memory usage patterns\",\"type\":\"text\"}]}]},{\"type\":\"list_item\",\"content\":[{\"type\":\"paragraph\",\"content\":[{\"text\":\"User experience\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\", such as customer satisfaction (CSAT) scores \",\"type\":\"text\"}]}]},{\"type\":\"list_item\",\"content\":[{\"type\":\"paragraph\",\"content\":[{\"text\":\"Business performance, such as revenue impact during degraded performance\",\"type\":\"text\"}]}]}]},{\"type\":\"paragraph\",\"content\":[{\"text\":\"In microservices environments, internal developer portals (IDPs) help track service health across numerous components. They help teams maintain visibility into \",\"type\":\"text\"},{\"text\":\"service performance\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" and quickly identify potential issues before they impact customers.\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":2},\"content\":[{\"text\":\"Best practices for implementing \",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]},{\"text\":\"SLOs\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"},{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]}]},{\"type\":\"paragraph\",\"content\":[{\"text\":\"Teams often struggle with inconsistent measurement, unclear ownership, and difficulty maintaining \",\"type\":\"text\"},{\"text\":\"SLOs\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" as systems evolve. These best practices will help set up your \",\"type\":\"text\"},{\"text\":\"SLOs\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" for success:\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":3},\"content\":[{\"text\":\"Use an internal developer portal\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"content\":[{\"text\":\"An IDP serves as the single source of truth for your \",\"type\":\"text\"},{\"text\":\"SLOs\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" by centralizing all definitions and current performance \",\"type\":\"text\"},{\"text\":\"metrics\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" in one location. It helps teams track service \",\"type\":\"text\"},{\"text\":\"dependencies\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" and their impact on composite \",\"type\":\"text\"},{\"text\":\"SLOs\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" while automating essential reporting and alert management functions. Teams can see the historical context for \",\"type\":\"text\"},{\"text\":\"SLO\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" decisions, so they can make informed decisions about future modifications.\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":3},\"content\":[{\"text\":\"Automate \",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]},{\"text\":\"SLO\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"},{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" tracking\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"content\":[{\"text\":\"Implement automated data collection for all \",\"type\":\"text\"},{\"text\":\"SLIs\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" to ensure tracking is consistent and reliable. \",\"type\":\"text\"},{\"text\":\"Real-time\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" dashboards and intelligent alerting based on \",\"type\":\"text\"},{\"text\":\"error budget\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" burn rates help teams identify issues before they become critical. \",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":3},\"content\":[{\"text\":\"Establish clear ownership\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"content\":[{\"text\":\"Assign primary team responsibility for each \",\"type\":\"text\"},{\"text\":\"SLO\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" and define explicit ownership for shared \",\"type\":\"text\"},{\"text\":\"dependencies\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" to prevent confusion during incidents. Create clear escalation paths for \",\"type\":\"text\"},{\"text\":\"SLO\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" breaches that specify who should be notified and when.\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":3},\"content\":[{\"text\":\"Involve \",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]},{\"text\":\"stakeholders\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"},{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" early\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"content\":[{\"text\":\"Include \",\"type\":\"text\"},{\"text\":\"product managers\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" in \",\"type\":\"text\"},{\"text\":\"SLO target\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" discussions to ensure alignment with \",\"type\":\"text\"},{\"text\":\"business goals\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" and \",\"type\":\"text\"},{\"text\":\"customer expectations\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\". Customer success teams can give valuable perspective on user impact, so involve them early on and regularly review \",\"type\":\"text\"},{\"text\":\"SLOs\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" to make sure they're aligned with business priorities. \",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":3},\"content\":[{\"text\":\"Segment \",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]},{\"text\":\"SLOs\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"},{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" by service type\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"content\":[{\"text\":\"Define service tiers based on business impact and set appropriate \",\"type\":\"text\"},{\"text\":\"SLOs\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" for each tier rather than applying one-size-fits-all targets. Consider regional variations in service requirements and account for different customer segments when setting reliability targets. This helps teams focus their reliability efforts where they matter most.\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":3},\"content\":[{\"text\":\"Incorporate redundancy\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"content\":[{\"text\":\"Build reliability into your architecture by implementing circuit breakers for critical \",\"type\":\"text\"},{\"text\":\"dependencies\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" and deploying services across multiple availability zones. Design systems for graceful degradation with fallback options for critical functionality to maintain \",\"type\":\"text\"},{\"text\":\"service availability\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" even during partial \",\"type\":\"text\"},{\"text\":\"outages\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\".\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":3},\"content\":[{\"text\":\"Document and communicate\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"content\":[{\"text\":\"Maintain up-to-date \",\"type\":\"text\"},{\"text\":\"SLO\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" definitions and measurement methods in a central location accessible to all teams. Create clear incident response playbooks that guide teams through common failure scenarios and share regular \",\"type\":\"text\"},{\"text\":\"SLO\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" performance reports to maintain visibility across the organization.\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":2},\"content\":[{\"text\":\"Set up accurate \",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]},{\"text\":\"SLOs\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"},{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" fast with Cortex\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"content\":[{\"text\":\"While implementing \",\"type\":\"text\"},{\"text\":\"SLOs\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" can be complex, the right tooling makes a difference in setup and maintenance. Cortex helps teams implement and manage \",\"type\":\"text\"},{\"text\":\"SLOs\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" effectively across their microservices architecture. Here's how leading teams are using Cortex to improve their \",\"type\":\"text\"},{\"text\":\"SLOs\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\":\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":3},\"content\":[{\"text\":\"Engineering excellence through connected insights\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"content\":[{\"text\":\"Cortex connects engineering output to business outcomes by providing comprehensive visibility into system and team performance. The \",\"type\":\"text\"},{\"text\":\"Eng Intelligence feature\",\"type\":\"text\",\"marks\":[{\"type\":\"link\",\"attrs\":{\"href\":\"https://www.cortex.io/products/eng-intelligence\",\"uuid\":null,\"anchor\":null,\"target\":null,\"linktype\":\"url\"}}]},{\"text\":\" leverages your existing \",\"type\":\"text\"},{\"text\":\"SLO\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" data to help teams measure and improve their effectiveness. This \",\"type\":\"text\"},{\"text\":\"integration\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" between reliability \",\"type\":\"text\"},{\"text\":\"metrics\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" and team performance creates a feedback loop that drives continuous improvement and engineering excellence.\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":3},\"content\":[{\"text\":\"Unified service visibility\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"content\":[{\"text\":\"Cortex's service catalog\",\"type\":\"text\",\"marks\":[{\"type\":\"link\",\"attrs\":{\"href\":\"https://www.cortex.io/products/catalog\",\"uuid\":null,\"anchor\":null,\"target\":null,\"linktype\":\"url\"}}]},{\"text\":\" provides a complete view of your microservices landscape in a single location. Teams can visualize service \",\"type\":\"text\"},{\"text\":\"dependencies\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\", track ownership, and monitor critical \",\"type\":\"text\"},{\"text\":\"metrics\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" from one central dashboard. This helps teams understand how their \",\"type\":\"text\"},{\"text\":\"SLOs\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" interact with dependent services and quickly identify potential reliability issues before they affect customers.\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":3},\"content\":[{\"text\":\"Automated reliability tracking\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"content\":[{\"text\":\"Cortex automates tracking \",\"type\":\"text\"},{\"text\":\"SLO\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" compliance through scorecards that continuously evaluate service health against predefined objectives. Teams receive \",\"type\":\"text\"},{\"text\":\"real-time\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" insights into \",\"type\":\"text\"},{\"text\":\"service performance\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" and can quickly identify when services drift from their reliability targets.\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":3},\"content\":[{\"text\":\"Streamlined incident management\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"content\":[{\"text\":\"When incidents occur, context is critical. Cortex integrates with your existing \",\"type\":\"text\"},{\"text\":\"incident management\",\"type\":\"text\",\"marks\":[{\"type\":\"link\",\"attrs\":{\"href\":\"https://www.cortex.io/solutions/incident-management\",\"uuid\":null,\"anchor\":null,\"target\":null,\"linktype\":\"url\"}}]},{\"text\":\" tools to provide immediate access to relevant service information, \",\"type\":\"text\"},{\"text\":\"dependencies\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\", and historical performance data. Teams can correlate \",\"type\":\"text\"},{\"text\":\"SLO\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" breaches with root causes more quickly, leading to faster resolution times and more effective post-incident learning.\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":3},\"content\":[{\"text\":\"Production readiness assessment\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"content\":[{\"text\":\"Before setting \",\"type\":\"text\"},{\"text\":\"SLOs\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\", teams need confidence that their services are ready for production traffic. Cortex provides built-in tools for assessing service \",\"type\":\"text\"},{\"text\":\"production readiness\",\"type\":\"text\",\"marks\":[{\"type\":\"link\",\"attrs\":{\"href\":\"https://www.cortex.io/post/how-to-create-a-great-production-readiness-checklist\",\"uuid\":null,\"anchor\":null,\"target\":null,\"linktype\":\"url\"}}]},{\"text\":\", ensuring all necessary components and \",\"type\":\"text\"},{\"text\":\"metrics\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" are in place. This systematic approach helps teams set realistic and achievable \",\"type\":\"text\"},{\"text\":\"SLOs\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" while maintaining high reliability standards.\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":3},\"content\":[{\"text\":\"Standardized \",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]},{\"text\":\"SLO\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"},{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" implementation\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"content\":[{\"text\":\"Consistency\",\"type\":\"text\",\"marks\":[{\"type\":\"link\",\"attrs\":{\"href\":\"https://www.cortex.io/post/improve-velocity-and-reliability-through-service-standardization\",\"uuid\":null,\"anchor\":null,\"target\":null,\"linktype\":\"url\"}}]},{\"text\":\" in \",\"type\":\"text\"},{\"text\":\"SLO\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" implementation becomes increasingly important as your service count grows. Cortex's platform provides templates and workflow \",\"type\":\"text\"},{\"text\":\"automation\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" that help teams standardize their approach to \",\"type\":\"text\"},{\"text\":\"SLO\",\"type\":\"text\",\"marks\":[{\"type\":\"textStyle\",\"attrs\":{\"color\":\"\"}}]},{\"text\":\" definition and management. 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Over the coming weeks we're examining each pillar of the DRIVE framework in turn. For the complete model, download the \",\"type\":\"text\",\"marks\":[{\"type\":\"italic\"}]},{\"text\":\"full DRIVE framework\",\"type\":\"text\",\"marks\":[{\"type\":\"link\",\"attrs\":{\"href\":\"https://www.cortex.io/report/drive-framework\",\"uuid\":null,\"anchor\":null,\"target\":\"_blank\",\"linktype\":\"url\"}},{\"type\":\"italic\"}]},{\"text\":\". Our last post covered \",\"type\":\"text\",\"marks\":[{\"type\":\"italic\"}]},{\"text\":\"Initiatives\",\"type\":\"text\",\"marks\":[{\"type\":\"link\",\"attrs\":{\"href\":\"https://www.cortex.io/post/drive-deep-dive-initiatives\",\"uuid\":null,\"anchor\":null,\"target\":\"_blank\",\"linktype\":\"url\"}},{\"type\":\"italic\"}]},{\"text\":\". Up next: Efficiency.\",\"type\":\"text\",\"marks\":[{\"type\":\"italic\"}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"---\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"The bottleneck on writing code is gone, and the industry is responding the way it always does when a constraint disappears: by producing more. Every new service, every new dependency, and every line an agent writes on a developer's behalf is also new surface area for something to go wrong.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"According to \",\"type\":\"text\"},{\"text\":\"NIST\",\"type\":\"text\",\"marks\":[{\"type\":\"link\",\"attrs\":{\"href\":\"https://www.nist.gov/news-events/news/2026/04/nist-updates-nvd-operations-address-record-cve-growth\",\"uuid\":null,\"anchor\":null,\"target\":\"_blank\",\"linktype\":\"url\"}}]},{\"text\":\", CVE submissions to the National Vulnerability Database increased 263% between 2020 and 2025, a trend the agency does not expect to let up. The volume got large enough that NIST announced in April 2026 it would stop trying to fully analyze every incoming CVE, prioritizing only vulnerabilities already confirmed as actively exploited, software used by the federal government, and software defined as critical under Executive Order 14028. Everything else still gets published. It just doesn't get scored.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Code generation is only compounding the problem. A large and stubborn share of AI-generated code samples introduce \",\"type\":\"text\"},{\"text\":\"OWASP Top 10\",\"type\":\"text\",\"marks\":[{\"type\":\"link\",\"attrs\":{\"href\":\"https://owasp.org/www-project-top-ten/\",\"uuid\":null,\"anchor\":null,\"target\":\"_blank\",\"linktype\":\"url\"}}]},{\"text\":\" vulnerabilities, a rate that hasn't meaningfully improved across recent testing cycles.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"None of this is because security teams lack data. If anything, they drown in it: scanners, checklists, controls, more signal than any one person can act on in a leadership review. The problem is that raw volume doesn't answer the question leadership actually needs answered: Is risk accumulating, or is it being retired? That's a governance question, not a technical one, close to word-for-word what the \",\"type\":\"text\"},{\"text\":\"National Association of Corporate Directors\",\"type\":\"text\",\"marks\":[{\"type\":\"link\",\"attrs\":{\"href\":\"https://www.nacdonline.org/all-governance/governance-resources/governance-research/director-handbooks/2026-cyber-risk-oversight/cyber-risk-handbook-toolkit-2026/board-level-cybersecurity-metrics/\",\"uuid\":null,\"anchor\":null,\"target\":\"_blank\",\"linktype\":\"url\"}}]},{\"text\":\" is now telling boards to ask for: not raw technical detail, but a small set of business-aligned metrics tied to risk acceptance and accountability. This is where DRIVE's Vigilance pillar begins.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Are we actively defending our systems and managing our acceptable risk?\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"heading\",\"attrs\":{\"level\":2,\"textAlign\":null},\"content\":[{\"text\":\"What Vigilance measures\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Vigilance is grounded in the assets that actually matter to customers and regulators: the services, repositories, and infrastructure components that hold customer data, process payments, or sit on a critical path. Everything else is noise for the purposes of a leadership review, even if it's worth tracking at the team level.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Three critical metrics cover the pillar from three different angles: \",\"type\":\"text\"}]},{\"type\":\"bullet_list\",\"content\":[{\"type\":\"list_item\",\"content\":[{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Fixable Critical and High CVEs past SLA\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]},{\"text\":\": measures exposure that's already known and already actionable, the risk an organization is choosing not to close. \",\"type\":\"text\"}]}]},{\"type\":\"list_item\",\"content\":[{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Assets below the compliance baseline\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]},{\"text\":\": measures whether the org's own minimum bar for security and operational hygiene is actually being met. \",\"type\":\"text\"}]}]},{\"type\":\"list_item\",\"content\":[{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Orphaned and unverified assets\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]},{\"text\":\": measure something neither of the first two can: risk with no human accountable for it at all.\",\"type\":\"text\"}]}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Together, the three answer the pillar question holistically without having to read a raw vulnerability count or a control-by-control audit.\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":3,\"textAlign\":null},\"content\":[{\"text\":\"Open Critical/High fixable CVEs\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Counted as the sum of open Critical and High severity vulnerabilities with a known upstream fix, rolled up per domain.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"The scope is drawn deliberately narrow. Below High severity, prioritization gets too org-specific for a leadership review: a Medium in a payments service isn't the same risk as a Medium in an internal dev tool, and that distinction belongs at the team level, not the OpEx review. The \\\"fixable\\\" qualifier matters just as much. If no fix exists yet, there's no remediation path to hold anyone accountable to, and it belongs on a separate risk-acceptance surface rather than the weekly scorecard.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Just a simple count doesn’t provide a meaningful “red” signal; it's how much of that count has breached SLA (a defensible default is 30 days for Critical, 60 days for High). Say a domain is sitting on 7 open Critical and 21 open High vulnerabilities, 28 total. On its own, that number tells a room of leaders almost nothing: is it bad, is it normal, has it always looked like this? The breakdown is what turns it into a signal. If one of those Criticals has been open 41 days and three of the Highs have been open past 70, that's four SLA breaches out of 28, and it's the four that flag the domain red. The conversation that follows isn't \\\"why do you have 28 vulnerabilities.\\\" It's \\\"who owns these four, and why are they still open.\\\"\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":3,\"textAlign\":null},\"content\":[{\"text\":\"Assets not meeting the compliance baseline\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Counted as the number of services failing at least one rule in the org's defined compliance or security baseline, rolled up as passing/failing counts through each reporting level.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Most compliance frameworks run to hundreds of individual controls, and walking through each one in a leadership meeting is neither practical nor useful; nobody's attention span survives a control-by-control readout, and nobody in the room needs that level of detail to decide where to push. DRIVE's objective here is to define a baseline instead: a small, explicit set of requirements every in-scope asset must meet. For a service, that might mean a named owner, a curated SLO, a linked runbook, and a supported package version. Infrastructure assets will have a different baseline entirely. DRIVE doesn't prescribe what belongs in it, it just requires that whatever baseline a scorecard enforces is stated plainly, so everyone reviewing the number knows exactly what \\\"failing\\\" means.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"The red signal is a pass rate below threshold, a defensible default being 90% of Tier 1 services passing. Compliance tends to be an easier conversation than the other two Vigilance metrics, mostly because the pain is already felt by the time it reaches the review; teams already know when their audit prep is a scramble. The value from DRIVE isn’t necessarily a simple audit, it's the baseline framing: instead of relitigating which controls matter every cycle, the review just asks whether the assets that are supposed to clear the bar are actually clearing it, and for which tier that's slipping.\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":3,\"textAlign\":null},\"content\":[{\"text\":\"Orphaned and unverified assets\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Counted as services with no valid owner, plus services whose listed owner hasn't reverified ownership within a defined window (every six months is a reasonable default). For organizations under heavier regulatory scrutiny, unverified should be treated as functionally equivalent to unowned rather than as a lesser category.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"This is the risk category with no human accountability attached at all. A repo carrying a Critical CVE and no owner has no one to prioritize it, so it sits untouched until an incident forces the question. Then everyone is scrambling to answer it at once.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"The rollup here works differently than the other two metrics. It's counted by domain or by criticality tier only, never rolled up to a team, because an orphaned service has no team to roll up to by definition. The red signal is correspondingly blunt: any count above zero for Tier 0 or critical-path services is a problem, full stop.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"This tends to be the metric that delivers the most value the first time an organization actually runs it. Most orgs have more orphaned services than they think they do, and simply surfacing the list is usually the first real step toward repairing the ownership graph, well before any of the fixing starts.\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":2,\"textAlign\":null},\"content\":[{\"text\":\"Secondary drag metrics\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"A longer tail of risk lives below the three critical signals: lower-severity issues that accumulate quietly between cycles, and the process breakdowns that let them pile up in the first place. These belong in team-level drill-downs, not the leadership scorecard.\",\"type\":\"text\"}]},{\"type\":\"bullet_list\",\"content\":[{\"type\":\"list_item\",\"content\":[{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Open Medium and Low CVEs\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]},{\"text\":\" are worth tracking for team-level trend awareness, for the same reason they're excluded from the critical metrics: prioritization below High severity is too org-specific to mean anything in aggregate at the leadership level.\",\"type\":\"text\"}]}]},{\"type\":\"list_item\",\"content\":[{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"A single count of SLA breaches across all severities\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]},{\"text\":\" is a useful integrity check on the remediation process as a whole, distinct from whether the top-severity items specifically are closing. If that number is climbing even while Critical and High stay green, it's an early signal that the process is degrading before it shows up where leadership is looking.\",\"type\":\"text\"}]}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Not every organization needs every drag metric running from day one. Start with the three critical signals, and add these once a specific pain point makes the case for going deeper.\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":2,\"textAlign\":null},\"content\":[{\"text\":\"Where existing security frameworks fit\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Vigilance isn't a replacement for the scanners and compliance programs most security teams already run. Vulnerability scanners, SOC 2 and ISO control audits, and other regulatory frameworks are still doing the measurement work, and they're good at it. What they don't do on their own is force a recurring, resourced decision about what to do with what they find.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"That's the layer DRIVE adds. The OpEx review takes what a scanner flags, what an audit fails, and what a control framework requires, and turns it into the same kind of recurring leadership attention and resource reallocation the other DRIVE pillars get. A scanner can tell a team a service has a Critical vulnerability. It can't put that vulnerability in front of the people who decide whether the team gets time to fix it this week or next quarter. \",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":2,\"textAlign\":null},\"content\":[{\"text\":\"Measuring Vigilance in an OpEx review\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"The Operational Excellence review is where these three signals actually get read against threshold and turned into redirected attention and resourcing.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"In practice, the review is chasing three things:\",\"type\":\"text\"}]},{\"type\":\"ordered_list\",\"attrs\":{\"order\":1},\"content\":[{\"type\":\"list_item\",\"content\":[{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Which owners are holding the SLA-breaching CVEs\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]},{\"text\":\" and why those specific ones are still open past the deadline the org set for itself.\",\"type\":\"text\"}]}]},{\"type\":\"list_item\",\"content\":[{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Where the compliance baseline pass rate is slipping\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]},{\"text\":\" and for which tier, since a dip in Tier 2 coverage is a very different conversation than the same dip in Tier 1.\",\"type\":\"text\"}]}]},{\"type\":\"list_item\",\"content\":[{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Whether there's a Tier 0 orphan anywhere in the org\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]},{\"text\":\" treated as a stop-the-line item rather than a line item, the same way a Sev0 incident would.\",\"type\":\"text\"}]}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"None of these require the review to relitigate the underlying scanner data or compliance audit itself. The review's job is narrower and more useful: turn a red signal into a named owner and a next action before the meeting ends.\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":2,\"textAlign\":null},\"content\":[{\"text\":\"Where the Vigilance signals come together\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"These three signals rarely come from one place. They're split across a handful of disconnected systems: a scanner tracking CVEs, a separate compliance tool checking controls, a catalog (if one exists) tracking services, and whatever spreadsheet or wiki page is doing double duty as an ownership record. Pulling one domain's Vigilance numbers together for a review often means someone manually reconciling all four before the meeting even starts.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Cortex closes that gap automatically. \",\"type\":\"text\"},{\"text\":\"Scorecards\",\"type\":\"text\",\"marks\":[{\"type\":\"link\",\"attrs\":{\"href\":\"https://www.cortex.io/products/scorecard\",\"uuid\":null,\"anchor\":null,\"target\":\"_blank\",\"linktype\":\"url\"}}]},{\"text\":\" codify whatever compliance baseline an org defines and grade every service against it automatically, rather than requiring a manual audit pass each cycle. The \",\"type\":\"text\"},{\"text\":\"Context Graph\",\"type\":\"text\",\"marks\":[{\"type\":\"link\",\"attrs\":{\"href\":\"https://www.cortex.io/products/context-graph\",\"uuid\":null,\"anchor\":null,\"target\":\"_blank\",\"linktype\":\"url\"}}]},{\"text\":\", paired with ownership prediction, is what actually surfaces orphaned and unverified assets, since it's built to know which services exist and who's supposed to be accountable for them, not just which ones a team remembered to register. When a new CVE drops, Cortex's \",\"type\":\"text\"},{\"text\":\"Catalog\",\"type\":\"text\",\"marks\":[{\"type\":\"link\",\"attrs\":{\"href\":\"https://www.cortex.io/products/catalog\",\"uuid\":null,\"anchor\":null,\"target\":\"_self\",\"linktype\":\"url\"}}]},{\"text\":\" returns the affected-services list immediately and tracks remediation per team as an Initiative, so the fix itself gets the same visibility and follow-through as any other org-wide effort. From there, \",\"type\":\"text\"},{\"text\":\"Engineering Intelligence\",\"type\":\"text\",\"marks\":[{\"type\":\"link\",\"attrs\":{\"href\":\"https://www.cortex.io/products/eng-intelligence\",\"uuid\":null,\"anchor\":null,\"target\":\"_blank\",\"linktype\":\"url\"}}]},{\"text\":\" turns it into the report leadership actually reviews at OpEx..\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Rapid7\",\"type\":\"text\",\"marks\":[{\"type\":\"link\",\"attrs\":{\"href\":\"https://www.cortex.io/case-studies/rapid7\",\"uuid\":null,\"anchor\":null,\"target\":\"_blank\",\"linktype\":\"url\"}}]},{\"text\":\" is a useful illustration of what this looks like once it's running end to end: a security company using Cortex to manage the same ownership and compliance visibility problems Vigilance is meant to solve for engineering orgs generally. In one case, this let Rapid7 migrate 3,000 database instances across regions in under two weeks; work that would otherwise have taken months.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Interested in learning more about DRIVE? \",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]},{\"text\":\"Take the \",\"type\":\"text\"},{\"text\":\"DRIVE maturity assessment\",\"type\":\"text\",\"marks\":[{\"type\":\"link\",\"attrs\":{\"href\":\"https://www.cortex.io/drive/assessment\",\"uuid\":null,\"anchor\":null,\"target\":\"_self\",\"linktype\":\"url\"}}]},{\"text\":\" to see where your organization stands against the Vigilance pillar and the rest of the DRIVE framework. \",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Next in the series: Efficiency, the pillar that asks how capacity is split between innovation and maintenance.\",\"type\":\"text\"}]}]},\"customer\":[],\"metadata\":[{\"og\":[{\"_uid\":\"8c153e2d-12c3-4859-bf0e-96094e43e2ef\",\"image\":{\"id\":200656737140922,\"alt\":\"\",\"name\":\"\",\"focus\":\"\",\"title\":\"\",\"source\":\"\",\"filename\":\"https://a-us.storyblok.com/f/1021527/3840x2040/e910d083c1/vigilance.png\",\"copyright\":\"\",\"fieldtype\":\"asset\",\"meta_data\":{},\"is_external_url\":false},\"title\":\"DRIVE Deep Dive: Vigilance\",\"component\":\"meta_fields\",\"description\":\"Vigilance is the DRIVE pillar for security governance. 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SRE was the operations function's answer to scale: how to keep systems reliable when the systems get big. Platform answered a different problem: how to let developers ship without becoming infrastructure experts. Security drew the line on what could safely reach production.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"That arrangement held for the better part of fifteen years. When humans wrote every line of code, three teams could draft separate guidelines, ship separate tools, and meet occasionally to negotiate the trade-offs between them. AI breaks that arrangement. A senior engineer with a coding agent now often ships in days what a team used to ship in weeks. Yet most engineering organizations report moving only about \",\"type\":\"text\"},{\"text\":\"20% faster overall\",\"type\":\"text\",\"marks\":[{\"type\":\"link\",\"attrs\":{\"href\":\"https://www.cortex.io/post/ai-is-making-engineering-faster-but-not-better-state-of-ai-benchmark-2026\",\"uuid\":null,\"anchor\":null,\"target\":\"_blank\",\"linktype\":\"url\"}}]},{\"text\":\". The individual speedup leaks out in coordination before it reaches production. AI-generated code removes latency, and trade-off discussions need to happen more frequently.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"On a recent episode of the \",\"type\":\"text\"},{\"text\":\"Braintrust podcast\",\"type\":\"text\",\"marks\":[{\"type\":\"link\",\"attrs\":{\"href\":\"https://www.cortex.io/podcasts/meeting-ai-with-ai-how-platform-sre-and-security-are-converging-with-okta-s-dinesh-sukhija\",\"uuid\":null,\"anchor\":null,\"target\":\"_blank\",\"linktype\":\"url\"}}]},{\"text\":\", Dinesh Sukhija, Director of Engineering at Okta, put the question directly: \",\"type\":\"text\"}]},{\"type\":\"blockquote\",\"content\":[{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"\\\"Maybe it's time to bring the teams together under one leadership now.\\\"\",\"type\":\"text\"}]}]},{\"type\":\"heading\",\"attrs\":{\"level\":2,\"textAlign\":null},\"content\":[{\"text\":\"Cost shows up in the trade-offs that nobody owns\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Reliability and cost are a single conversation. Every additional nine of availability has a cost. When SRE owns reliability and a separate FinOps function owns cost, the trade-off happens in a shared spreadsheet weeks after the architecture is committed.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Security and developer flow are the same. Guardrails that are too tight slow shipping; too loose, and credentials end up on GitHub. When security writes policy in isolation from the platform team that has to enforce it, the policy gets watered down, ignored, or routed around.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Observability and incident response can't really be pulled apart either. Service-level standardization makes incidents shorter: the same dashboard layout, the same SLO definitions, the same on-call runbook across every service mean less cognitive load when something breaks. When those standards live in three different orgs, no one team can hold them.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"The tensions are old, but the frequency is new. A trade-off revisited every six weeks under human-paced delivery gets revisited every day when agents are committing code. At that frequency, cross-org coordination becomes friction. Each leader is doing exactly their job. The gap is that nobody owns the decisions \",\"type\":\"text\"},{\"text\":\"between\",\"type\":\"text\",\"marks\":[{\"type\":\"italic\"}]},{\"text\":\" their jobs.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Dinesh described the same shift from the practitioner's seat:\",\"type\":\"text\"}]},{\"type\":\"blockquote\",\"content\":[{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"\\\"Complexity shifts upwards now. You're not just worried about your algorithms or your core code or the guts of the code, but you're worried about the ecosystem now.\\\"\",\"type\":\"text\"}]}]},{\"type\":\"heading\",\"attrs\":{\"level\":2,\"textAlign\":null},\"content\":[{\"text\":\"Critical requirements for merging the functions\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Closing that gap is what Dinesh is reaching for when he floats merging the teams. But the reporting lines are the surface. Whatever they look like, the response only holds if three things are true underneath.\",\"type\":\"text\"}]},{\"type\":\"ordered_list\",\"attrs\":{\"order\":1},\"content\":[{\"type\":\"list_item\",\"content\":[{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Someone owns the trade-offs between the functions. One accountability for the calls where reliability, cost, and security collide, rather than three leaders brokering across calendars.\",\"type\":\"text\"}]}]},{\"type\":\"list_item\",\"content\":[{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Every service has a single source of truth: ownership, dependencies, on-call, SLOs, security posture, and cost in one catalog, kept current by automation rather than manual entry. The catalog is the substrate the consolidated function operates on.\",\"type\":\"text\"}]}]},{\"type\":\"list_item\",\"content\":[{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"One definition of production-ready covers all three focus areas. Reliability, security, and operational maturity sit in the same scorecard, evaluated continuously, with the same enforcement model. Teams know what \\\"ready\\\" means before they ship, not after review.\",\"type\":\"text\"}]}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Partial versions are already observable in the field. At \",\"type\":\"text\"},{\"text\":\"The New York Times,\",\"type\":\"text\",\"marks\":[{\"type\":\"link\",\"attrs\":{\"href\":\"https://www.cortex.io/podcasts/building-a-developer-platform-like-a-product-inside-the-new-york-times-with-sneha-rao-and-ahmed-bebars\",\"uuid\":null,\"anchor\":null,\"target\":\"_blank\",\"linktype\":\"url\"}}]},{\"text\":\" SRE and FinOps sit inside Developer Platforms because availability and cost are a single conversation. At Okta, Dinesh's mandate spans SRE, security infrastructure, and enterprise security tooling for the same reason.\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":2,\"textAlign\":null},\"content\":[{\"text\":\"A name for the missing scope\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"We've been calling it \",\"type\":\"text\"},{\"text\":\"Engineering Operations\",\"type\":\"text\",\"marks\":[{\"type\":\"link\",\"attrs\":{\"href\":\"https://www.cortex.io/post/what-is-engineering-operations-a-guide-to-the-discipline-transforming-software-teams\",\"uuid\":null,\"anchor\":null,\"target\":\"_blank\",\"linktype\":\"url\"}}]},{\"text\":\": a single function accountable for the operating system of the engineering org, including the service catalog, the standards, the scorecards, and the trade-offs across reliability, security, cost, and delivery. A security team still draws the line. The difference is that the line gets drawn in the same room where reliability and cost are decided, instead of in a downstream review.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Every other major function got its operational counterpart years ago. Sales has Sales Ops, marketing has Marketing Ops, finance and product have theirs. Engineering, usually the largest cost center in the building, never did. The market is closing that gap now: companies like Block, WHOOP, Microsoft, and 1Password have stood up formal Engineering Operations functions and are hiring into them.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"How that function maps onto the org chart comes down to size. Under five hundred engineers, one strong technical leader can credibly hold platform, SRE, and security at once. That was Dinesh's case on the pod: for smaller orgs, the mandate to move fast favors putting them under one leader. Past that, span of control breaks and each area needs its own VP.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Whether you merge the teams is a question for your org chart. Whether anyone owns the trade-offs between them is a question for your next incident, your cloud bill, and your security posture.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Listen to the \",\"type\":\"text\"},{\"text\":\"full Braintrust episode\",\"type\":\"text\",\"marks\":[{\"type\":\"link\",\"attrs\":{\"href\":\"https://www.cortex.io/podcasts/meeting-ai-with-ai-how-platform-sre-and-security-are-converging-with-okta-s-dinesh-sukhija\",\"uuid\":null,\"anchor\":null,\"target\":\"_blank\",\"linktype\":\"url\"}}]},{\"text\":\" with Dinesh Sukhija on how platform, SRE, and security are converging in the AI era.\",\"type\":\"text\"}]}]},\"customer\":[],\"metadata\":[{\"og\":[{\"_uid\":\"9c623dd7-2779-4f4d-8dbb-5ba04cd88169\",\"image\":{\"id\":185400064579289,\"alt\":\"\",\"name\":\"\",\"focus\":\"\",\"title\":\"\",\"source\":\"\",\"filename\":\"https://a-us.storyblok.com/f/1021527/2880x1620/66902d7ab7/platform-sre-and-security-are-converging.png\",\"copyright\":\"\",\"fieldtype\":\"asset\",\"meta_data\":{},\"is_external_url\":false},\"title\":\"Should Platform, SRE, And Security Merge Into One Function?\",\"component\":\"meta_fields\",\"description\":\"When humans wrote every line of code, three teams could draft separate guidelines, ship separate tools, and meet occasionally to negotiate the trade-offs between them. 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Every line of should add value, while being careful to reduce opportunity for risk.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"This article explains what code quality is and how you can measure it. We'll look specifically at metrics that can indicate code quality, but will also consider the broader development environment and incentives that arise from all measurement.\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":3,\"textAlign\":null},\"content\":[{\"text\":\"What is code quality?\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Code quality refers to the measure of how well-written and well-structured a piece of software code is. It encompasses various aspects such as readability, maintainability, reliability, efficiency, and adherence to coding standards and best practices. Essentially, code quality reflects how easily a codebase can be understood, modified, and maintained by developers, as well as its ability to perform reliably and efficiently under different conditions.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"This does not exist in a vacuum. Code quality is dependent on various factors such as business goals, legibility and security. Good quality code is most helpful to software engineers, but improves user experience too as they are more likely to find your application reliable and \",\"type\":\"text\"},{\"text\":\"secure\",\"type\":\"text\",\"marks\":[{\"type\":\"link\",\"attrs\":{\"href\":\"https://www.cortex.io/post/securing-your-microservices-architecture\",\"uuid\":null,\"anchor\":null,\"target\":null,\"linktype\":\"url\"}}]},{\"text\":\".\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Code quality draws from a few properties:\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":3,\"textAlign\":null},\"content\":[{\"text\":\"Readability\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"This is somewhat self-explanatory, referring to how well-structured and understandable code is to developers. It is measured by examining factors such as naming conventions, documentation quality, and the complexity of constructs used. Good code readability facilitates easier maintenance, debugging, and refactoring, keeping variable names meaningful and functions small and efficient.\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":3,\"textAlign\":null},\"content\":[{\"text\":\"Maintainability\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Maintainability measures the ease with which software can be modified to fix defects, improve performance, or adapt to a changing environment. It's assessed through code complexity analyses, adherence to coding standards, and the modularity of the software architecture. High maintainability is crucial for extending the lifespan of software and reducing long-term costs associated with updates and enhancements.\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":3,\"textAlign\":null},\"content\":[{\"text\":\"Performance\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Performance in the context of software refers to how efficiently a software system responds to user actions, utilizes resources, and processes data. It is measured by metrics such as response time, throughput, and should consider efficiency and resource utilization as well as raw speed. Optimizing performance ensures that software applications can handle expected workloads smoothly and provide a satisfactory user experience.\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":3,\"textAlign\":null},\"content\":[{\"text\":\"Reliability\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Reliability measures the ability of software to perform its required functions under stated conditions for a specified period of time without failure. This attribute is quantified by tracking \",\"type\":\"text\"},{\"text\":\"software reliability metrics\",\"type\":\"text\",\"marks\":[{\"type\":\"link\",\"attrs\":{\"href\":\"https://www.cortex.io/post/how-to-choose-your-software-reliability-metrics\",\"uuid\":null,\"anchor\":null,\"target\":null,\"linktype\":\"url\"}}]},{\"text\":\", such as the frequency and severity of failures, mean time between failures (MTBF), and recovery time after a failure. High reliability is critical for maintaining user trust and minimizing disruptions in software-dependent activities, especially in critical systems where downtime can have significant consequences.\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":3,\"textAlign\":null},\"content\":[{\"text\":\"What are the characteristics of good code?\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Developers often cannot give a succinct definition of what represents bad code. But like the \",\"type\":\"text\"},{\"text\":\"Supreme Court\",\"type\":\"text\",\"marks\":[{\"type\":\"link\",\"attrs\":{\"href\":\"https://history.wustl.edu/i-know-it-when-i-see-it-history-obscenity-pornography-united-states\",\"uuid\":null,\"anchor\":null,\"target\":null,\"linktype\":\"url\"}}]},{\"text\":\" assessing pornography, they know it when they see it. It’s typically unreadable or confusing, prone to breaking and lacks proper documentation. It is poorly organized and devoid of a logical structure, leading to the term “\",\"type\":\"text\"},{\"text\":\"spaghetti code\",\"type\":\"text\",\"marks\":[{\"type\":\"link\",\"attrs\":{\"href\":\"https://en.wikipedia.org/wiki/Spaghetti_code\",\"uuid\":null,\"anchor\":null,\"target\":null,\"linktype\":\"url\"}}]},{\"text\":\"”. Reading it is like being in a maze without a map, and even small changes can cause it to break.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Good code is defined by clarity and function. It follows a consistent style, with structures and patterns that guide the developer through the code’s logic. When programmers write clean code with proper indentation and formatting it speeds up the development process and ultimately the time-to-market. It enables scrum and agile methodologies by being adaptable in changing environments.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Comprehensive documentation is part of good code, which enables maintenance and further development. High-quality code is also designed to be testable, meaning it supports validation of its functionality through testing. Reading good code is like strolling through a manicured garden, where plants are thoughtfully placed, paths are well-tended and the gardener has recorded maintenance details for future generations.\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":3,\"textAlign\":null},\"content\":[{\"text\":\"Why does code quality matter?\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Code quality influences not just the development process, but the security, performance and overall user experience of the final product. \",\"type\":\"text\"},{\"text\":\"Software quality\",\"type\":\"text\",\"marks\":[{\"type\":\"link\",\"attrs\":{\"href\":\"https://www.cortex.io/post/software-quality-metrics\",\"uuid\":null,\"anchor\":null,\"target\":null,\"linktype\":\"url\"}}]},{\"text\":\", \",\"type\":\"text\"},{\"text\":\"developer experience\",\"type\":\"text\",\"marks\":[{\"type\":\"link\",\"attrs\":{\"href\":\"https://www.cortex.io/post/why-developer-experience-matters\",\"uuid\":null,\"anchor\":null,\"target\":null,\"linktype\":\"url\"}}]},{\"text\":\" and user experience are all downstream of code quality, and getting it right makes for smoother interactions with faster response times for users. For developers, higher-quality code makes it easier to update legacy code, integrate new features and conduct code reviews. Solving for quality across every piece of code makes the development process more efficient while ensuring the longevity and success of the software project as a whole.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Today’s demands for quicker development cycles powered by continuous integration and DevOps principles make coding standards even more critical. Code quality is the foundation for software, and if you optimize every other part of the building process for speed and efficiency you’ll need to make sure the foundations are rock solid.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Benefits to code quality include:\",\"type\":\"text\"}]},{\"type\":\"bullet_list\",\"content\":[{\"type\":\"list_item\",\"content\":[{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Enhanced Reliability and Maintainability:\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]},{\"text\":\" High-quality code is robust and less prone to failures, making software systems more reliable. It also simplifies maintenance tasks, as the code is easier to understand and modify without introducing new errors.\",\"type\":\"text\"}]}]},{\"type\":\"list_item\",\"content\":[{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Software Stability:\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]},{\"text\":\" Quality code practices ensure that software behaves consistently under a range of conditions, reducing the likelihood of crashes or unexpected behavior.\",\"type\":\"text\"}]}]},{\"type\":\"list_item\",\"content\":[{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Faster Time to Market:\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]},{\"text\":\" By reducing the amount of time spent on debugging and reworking problematic code, projects can progress more rapidly from development to deployment.\",\"type\":\"text\"}]}]},{\"type\":\"list_item\",\"content\":[{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Cost Savings:\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]},{\"text\":\" Investing in code quality from the outset can significantly reduce long-term costs associated with software development. High-quality, maintainable code requires fewer resources to fix and update, leading to substantial savings over the software's lifecycle.\",\"type\":\"text\"}]}]},{\"type\":\"list_item\",\"content\":[{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Scalability and Adaptability:\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]},{\"text\":\" Quality code is designed with future growth in mind, making it easier to scale and adapt as requirements evolve. This ensures that the software can accommodate increasing loads and changing needs without extensive rewrites.\",\"type\":\"text\"}]}]},{\"type\":\"list_item\",\"content\":[{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Compliance and Security:\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]},{\"text\":\" Adhering to high code quality standards helps in meeting regulatory compliance requirements and enhancing software security. Well-structured, clean code is less vulnerable to security breaches and more likely to align with industry regulations.\",\"type\":\"text\"}]}]}]},{\"type\":\"heading\",\"attrs\":{\"level\":2,\"textAlign\":null},\"content\":[{\"text\":\"How can teams review code quality?\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"It’s crucial that code quality is checked and emphasized throughout the software development life cycle (SDLC). Using regular code reviews and code analysis tools at every step enables early detection, saving on costs and enabling a culture of continuous improvement.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Methods to review your code include:\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":3,\"textAlign\":null},\"content\":[{\"text\":\"Automated Quality Checks\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Definition\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Automated quality checks involve the use of software tools to automatically scan and analyze code for potential issues, such as syntax errors, security vulnerabilities, and code standard violations. These tools are integrated into the development process to ensure continuous assessment of code quality.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Pros/cons\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Pros include the ability to quickly scan large volumes of code, identify known issues with precision, and enforce coding standards consistently. However, automation may miss complex bugs that require human insight to detect and can generate false positives that need manual review.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"How it assesses different aspects of code quality\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Automated quality checks assess code quality by evaluating code against a predefined set of rules or standards. They can measure various aspects such as code complexity, adherence to coding conventions, potential security issues, and other factors that can affect maintainability, performance, and reliability.\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":3,\"textAlign\":null},\"content\":[{\"text\":\"Manual Code Reviews\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Definition\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Manual code reviews are a systematic examination of source code by developers other than the original author with the goal of finding bugs, ensuring adherence to coding standards, and improving code quality. More insights on best practices for code reviews can be found in \",\"type\":\"text\"},{\"text\":\"this article\",\"type\":\"text\",\"marks\":[{\"type\":\"link\",\"attrs\":{\"href\":\"https://www.cortex.io/post/best-practices-for-code-reviews\",\"uuid\":null,\"anchor\":null,\"target\":null,\"linktype\":\"url\"}}]},{\"text\":\".\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Pros/cons\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"The primary advantage of manual code reviews is the ability to catch complex code issues that automated tools might miss, including logical errors or issues with code clarity. Reviews also facilitate knowledge sharing among team members. The downside is that they can be time-consuming and depend heavily on the reviewers' expertise and biases.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"How it assesses different aspects of code quality\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Manual code reviews assess code quality by leveraging the insights and experience of human reviewers. They not only look for errors and potential improvements but also evaluate the readability, maintainability, and overall design of the code, offering a more nuanced understanding of its quality.\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":3,\"textAlign\":null},\"content\":[{\"text\":\"Static Analysis\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Definition\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Static analysis involves examining the code without executing it to find issues. It's a form of automated quality check known as static code analysis, focusing on identifying potential errors and vulnerabilities. For more details, refer to \",\"type\":\"text\"},{\"text\":\"this article\",\"type\":\"text\",\"marks\":[{\"type\":\"link\",\"attrs\":{\"href\":\"https://www.cortex.io/post/static-analysis-tools-everything-you-need-to-know\",\"uuid\":null,\"anchor\":null,\"target\":null,\"linktype\":\"url\"}}]},{\"text\":\" on static analysis tools.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Pros/cons\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Static analysis can efficiently identify certain types of errors, such as syntax errors, type mismatches, and known security vulnerabilities, across the entire codebase. However, it might not catch runtime errors or complex issues that manifest only under specific conditions. Additionally, like other automated methods, it can produce false positives.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"How it assesses different aspects of code quality\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Static analysis tools evaluate code quality by scanning the source code for patterns that are known to lead to errors, such as variables that have accidentally been reused or functions that are too long. They can also check for compliance with coding standards, analyze code complexity, and identify security vulnerabilities, thereby covering a wide range of quality aspects including readability, stability, and security. Storing results from static analyses can boost your \",\"type\":\"text\"},{\"text\":\"documentation efforts\",\"type\":\"text\",\"marks\":[{\"type\":\"link\",\"attrs\":{\"href\":\"https://www.cortex.io/post/how-to-strategically-approach-documenting-microservices\",\"uuid\":null,\"anchor\":null,\"target\":null,\"linktype\":\"url\"}}]},{\"text\":\". Most programming languages have their own \",\"type\":\"text\"},{\"text\":\"static analysis tools\",\"type\":\"text\",\"marks\":[{\"type\":\"link\",\"attrs\":{\"href\":\"https://www.cortex.io/post/static-analysis-tools-everything-you-need-to-know\",\"uuid\":null,\"anchor\":null,\"target\":null,\"linktype\":\"url\"}}]},{\"text\":\".\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Ensuring high quality code is not about finding the single best approach to tests and reviews. It means using multiple methodologies, metrics and assessments to measure code quality in a comprehensive way. In the next section we consider some metrics that can help.\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":2,\"textAlign\":null},\"content\":[{\"text\":\"Eight metrics to quantify code quality\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"heading\",\"attrs\":{\"level\":3,\"textAlign\":null},\"content\":[{\"text\":\"Cyclomatic Complexity\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Explanation\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]},{\"text\":\": This form of static analysis measures the complexity of a program by quantifying the number of linearly independent paths through it. Essentially, it is a prominent complexity metric to indicate how complex the control flow of the program is.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Example\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]},{\"text\":\": Calculated based on the graph theory of a program's control flow graph, a lower number suggests simpler code with fewer potential bugs, while a higher number indicates greater complexity and potentially more test cases required.\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":3,\"textAlign\":null},\"content\":[{\"text\":\"Maintainability Index\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Explanation\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]},{\"text\":\": This index assesses how easy it is to maintain the code on a scale of 0-100. It takes into account factors like extensibility, number of lines of code, cyclomatic complexity, and Halstead complexity measures.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Example\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]},{\"text\":\": A higher value (typically above 85) indicates better maintainability. It's calculated using a formula that combines several metrics, including volume of code, complexity, and comments. This helps identify areas where refactoring might reduce complexity.\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":3,\"textAlign\":null},\"content\":[{\"text\":\"Code Duplication\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Explanation\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]},{\"text\":\": Measures the amount of duplicated code within a codebase. High levels of duplication can make maintenance harder and leads to more bugs as there is an opportunity for divergent implementation of the same functionality.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Example\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]},{\"text\":\": Detected using tools that scan for identical or similar code blocks. Reducing duplication can significantly improve code quality by ensuring consistency and reducing potential points of failure.\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":3,\"textAlign\":null},\"content\":[{\"text\":\"Unit Test Pass Rate\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Explanation\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]},{\"text\":\": This metric indicates the percentage of unit tests that pass during a test run. It reflects the reliability of the code under test conditions.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Example\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]},{\"text\":\": A pass rate close to 100% is ideal. Lower rates may indicate problems in code logic or test coverage gaps, prompting further investigation.\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":3,\"textAlign\":null},\"content\":[{\"text\":\"Code Churn\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Explanation\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]},{\"text\":\": Code churn measures the frequency at which code is added, modified, or deleted within a repository. High churn rates can indicate instability or indecision within the development team.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Example\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]},{\"text\":\": Tracking code churn over time helps identify areas of the codebase that are frequently changing and may benefit from additional design reconsideration or testing.\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":3,\"textAlign\":null},\"content\":[{\"text\":\"Average Code Review Time\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Explanation\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]},{\"text\":\": This is a quantitative measurement of the average time taken for code reviews. Long review times can indicate complexity or lack of clarity, whereas very short times might suggest insufficient rigor.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Example\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]},{\"text\":\": Monitoring this metric can help teams understand and improve their review processes, aiming for thorough yet efficient reviews to maintain pace without sacrificing quality.\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":3,\"textAlign\":null},\"content\":[{\"text\":\"Technical Debt\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Explanation\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]},{\"text\":\": This quantifies the cost of choosing an easier or quicker solution in the short term instead of using a better approach that would take longer. High technical debt indicates that significant work is needed to improve the codebase.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Example\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]},{\"text\":\": There are various methods to calculate technical debt, but one common approach is to quantify the effort required to fix all maintainability issues. Improving these areas can reduce the long-term costs of a project. For more ways to measure technical debt, you can refer to \",\"type\":\"text\"},{\"text\":\"this article\",\"type\":\"text\",\"marks\":[{\"type\":\"link\",\"attrs\":{\"href\":\"https://hackernoon.com/how-to-measure-your-technical-debt-8-metrics-to-consider\",\"uuid\":null,\"anchor\":null,\"target\":null,\"linktype\":\"url\"}}]},{\"text\":\".\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":3,\"textAlign\":null},\"content\":[{\"text\":\"Dependency Graph Complexity\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Explanation\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]},{\"text\":\": This metric assesses the complexity of the dependency graph: the map of connections and relationships between components or modules in a codebase. A highly complex graph may indicate a tightly coupled system, which can make changes difficult and error-prone.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Example\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]},{\"text\":\": By analyzing the dependency graph, developers can identify overly complex interdependencies and consider refactoring to a more modular architecture, simplifying the structure and potentially improving maintainability and testability.\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":3,\"textAlign\":null},\"content\":[{\"text\":\"Tips for improving code quality\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Defining and measuring code quality is not an easy task, but even when you crack it your work is not done. Metrics reveal code quality, but they don’t improve it. Only by implementing changes through continuous improvement can you drive the results that improve code quality, and ultimately help stakeholders through faster time to market, improved \",\"type\":\"text\"},{\"text\":\"developer experience\",\"type\":\"text\",\"marks\":[{\"type\":\"link\",\"attrs\":{\"href\":\"https://www.cortex.io/post/why-developer-experience-matters\",\"uuid\":null,\"anchor\":null,\"target\":null,\"linktype\":\"url\"}}]},{\"text\":\" and greater cost savings.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"If this process is handled poorly it can actually have a negative effect. Increasing pressure on your team to deliver higher standards, without addressing their working environment and tooling, can lead to stress and burnout among your developers. Cynical employees may game the system, optimizing metrics at the expense of productivity and culture. There is a risk that your policies amount to “the beatings will continue until morale (code quality) improves”.\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"This risk is especially pronounced when you are not providing the right self-service options for developers. If they are unable to easily access the correct tools, documentation and support to improve their code then efforts to improve quality can make things worse. For a detailed explanation of this risk in the modern environment see \",\"type\":\"text\"},{\"text\":\"this blog\",\"type\":\"text\",\"marks\":[{\"type\":\"link\",\"attrs\":{\"href\":\"https://dev.to/jreock/developer-experience-is-dead-long-live-developer-experience-1col\",\"uuid\":null,\"anchor\":null,\"target\":null,\"linktype\":\"url\"}}]},{\"text\":\".\",\"type\":\"text\"}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Provided you are \",\"type\":\"text\"},{\"text\":\"getting your developer experience right\",\"type\":\"text\",\"marks\":[{\"type\":\"link\",\"attrs\":{\"href\":\"https://www.cortex.io/post/developer-experience-metrics-for-software-development-success\",\"uuid\":null,\"anchor\":null,\"target\":null,\"linktype\":\"url\"}}]},{\"text\":\", here are some tips to increase your code quality.\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":3,\"textAlign\":null},\"content\":[{\"text\":\"Follow coding standards\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"This is the most straightforward starting point. Adhering to coding standards ensures consistency, readability, and maintainability across the codebase. It simplifies the understanding of new and existing code for all developers, making it easier to identify errors, share code among team members, and onboard new developers.\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":3,\"textAlign\":null},\"content\":[{\"text\":\"Write meaningful documentation\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Good documentation acts as a roadmap for your code, explaining not just what the code does, but how and why certain decisions were made. This is crucial for maintenance, troubleshooting, and future development, as it allows developers to quickly understand and work with the code without having to examine it line by line.\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":3,\"textAlign\":null},\"content\":[{\"text\":\"Utilize version control\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Version control systems, such as Git, track and manage changes to the codebase, enabling multiple developers to work simultaneously without conflict. They also facilitate rollbacks to previous states and help in managing different versions of the code, making the development process more efficient and less prone to errors.\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":3,\"textAlign\":null},\"content\":[{\"text\":\"Perform code reviews\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Code reviews are a critical step in the software development process, allowing for shared knowledge among team members and early detection of potential issues. They encourage collaboration, improve code quality by catching bugs and logical errors early, and ensure adherence to coding standards and best practices.\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":3,\"textAlign\":null},\"content\":[{\"text\":\"Automate testing\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Automated tests verify the functionality of code quickly and efficiently, saving time and reducing the likelihood of human error. 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Continuous testing helps to maintain high-quality standards throughout the development process.\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":3,\"textAlign\":null},\"content\":[{\"text\":\"Set-up dashboards to increase visibility and collaboration\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Implementing dashboards through \",\"type\":\"text\"},{\"text\":\"internal developer portals\",\"type\":\"text\",\"marks\":[{\"type\":\"link\",\"attrs\":{\"href\":\"https://www.cortex.io/post/internal-developer-portal-vs-internal-developer-platform\",\"uuid\":null,\"anchor\":null,\"target\":null,\"linktype\":\"url\"}}]},{\"text\":\" can significantly enhance visibility and collaboration within development teams. The perfect solution should simplify the gathering and interpretation of data by the full range of developer tools in use, without overwhelming the team or requiring extensive administration after integration. These platforms help in tracking progress, identifying bottlenecks, and sharing insights across the team, fostering a culture of transparency and continuous improvement.\",\"type\":\"text\"}]},{\"type\":\"heading\",\"attrs\":{\"level\":2,\"textAlign\":null},\"content\":[{\"text\":\"Track and improve code with Cortex\",\"type\":\"text\",\"marks\":[{\"type\":\"bold\"}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"The Cortex IDP allows you define and track code quality metrics, but most importantly it embeds these in a system built for continuous improvement. Rather than setting orphaned metrics isolated from context, Cortex enables the transparency, developer collaboration and actionable insights needed to ensure your quality code is built in a setting that prioritizes developer experience and a culture of excellence. 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It helps your teams make data-driven decisions regarding code quality in the context of broader engineering initiatives.\",\"type\":\"text\"}]}]}]},{\"type\":\"bullet_list\",\"content\":[{\"type\":\"list_item\",\"content\":[{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Scorecards\",\"type\":\"text\",\"marks\":[{\"type\":\"link\",\"attrs\":{\"href\":\"https://www.cortex.io/products/scorecard\",\"uuid\":null,\"anchor\":null,\"target\":null,\"linktype\":\"url\"}},{\"type\":\"bold\"}]},{\"text\":\": Scorecards offer a comprehensive overview of service health and team performance across workflows. By pairing code quality metrics with broader indicators of overall quality, Scorecards give you an oversight that helps you to investigate the root cause of any drops in standards.\",\"type\":\"text\"}]},{\"type\":\"bullet_list\",\"content\":[{\"type\":\"list_item\",\"content\":[{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Take the self-guided Scorecards tour\",\"type\":\"text\",\"marks\":[{\"type\":\"link\",\"attrs\":{\"href\":\"https://app.demo.cortex.io/admin/scorecards?userpilot=ZXhwZXJpZW5jZTpybG1vaG82OVJZ\",\"uuid\":null,\"anchor\":null,\"target\":\"_blank\",\"linktype\":\"url\"}}]}]}]}]}]}]},{\"type\":\"bullet_list\",\"content\":[{\"type\":\"list_item\",\"content\":[{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Engineering Homepage\",\"type\":\"text\",\"marks\":[{\"type\":\"link\",\"attrs\":{\"href\":\"https://www.cortex.io/developer-homepage\",\"uuid\":null,\"anchor\":null,\"target\":null,\"linktype\":\"url\"}},{\"type\":\"bold\"}]},{\"text\":\": This personalized dashboard acts as a hub for developers, offering quick access to relevant metrics, reports, and tools. It decentralizes some of the responsibility for code quality standards, and ensures that relevant data and information is always at your developers' fingertips.\",\"type\":\"text\"}]},{\"type\":\"bullet_list\",\"content\":[{\"type\":\"list_item\",\"content\":[{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Take the self-guided Engineering Homepage tour\",\"type\":\"text\",\"marks\":[{\"type\":\"link\",\"attrs\":{\"href\":\"https://app.demo.cortex.io/admin/home?userpilot=ZXhwZXJpZW5jZTp5cnBIS2hfVUp6\",\"uuid\":null,\"anchor\":null,\"target\":\"_blank\",\"linktype\":\"url\"}}]}]}]}]}]}]},{\"type\":\"paragraph\",\"attrs\":{\"textAlign\":null},\"content\":[{\"text\":\"Cortex transforms the way development teams approach code quality and performance, by automating monitoring and goal tracking across each. 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